Topic: Structured bindings with polymorphic lambdas


Author: Curious <rmn100@gmail.com>
Date: Fri, 25 Aug 2017 10:36:51 -0700 (PDT)
Raw View
------=_Part_2873_1902952938.1503682611453
Content-Type: multipart/alternative;
 boundary="----=_Part_2874_1944788656.1503682611453"

------=_Part_2874_1944788656.1503682611453
Content-Type: text/plain; charset="UTF-8"

The idea is to support structured bindings with polymorphic lambdas, for
example:

std::for_each(map, [](auto [key,value]) { ... });

The previous post on this page was here
(https://groups.google.com/a/isocpp.org/forum/?fromgroups#!searchin/std-proposals/structured$20bindings$20/std-proposals/EsPJnQooPoI/24Gd4PGABgAJ)

And a formal paper proposing the idea has been attached to this post.

--
You received this message because you are subscribed to the Google Groups "ISO C++ Standard - Future Proposals" group.
To unsubscribe from this group and stop receiving emails from it, send an email to std-proposals+unsubscribe@isocpp.org.
To post to this group, send email to std-proposals@isocpp.org.
To view this discussion on the web visit https://groups.google.com/a/isocpp.org/d/msgid/std-proposals/b8d14aa1-adcb-41d9-8fe8-d70805927161%40isocpp.org.

------=_Part_2874_1944788656.1503682611453
Content-Type: text/html; charset="UTF-8"
Content-Transfer-Encoding: quoted-printable

<div dir=3D"ltr">The idea is to support structured bindings with polymorphi=
c lambdas, for example:<div><br></div><div><div class=3D"prettyprint" style=
=3D"background-color: rgb(250, 250, 250); border: 1px solid rgb(187, 187, 1=
87); word-wrap: break-word;"><code class=3D"prettyprint"><div class=3D"subp=
rettyprint"><span style=3D"color: #000;" class=3D"styled-by-prettify">std</=
span><span style=3D"color: #660;" class=3D"styled-by-prettify">::</span><sp=
an style=3D"color: #000;" class=3D"styled-by-prettify">for_each</span><span=
 style=3D"color: #660;" class=3D"styled-by-prettify">(</span><span style=3D=
"color: #000;" class=3D"styled-by-prettify">map</span><span style=3D"color:=
 #660;" class=3D"styled-by-prettify">,</span><span style=3D"color: #000;" c=
lass=3D"styled-by-prettify"> </span><span style=3D"color: #660;" class=3D"s=
tyled-by-prettify">[](</span><span style=3D"color: #008;" class=3D"styled-b=
y-prettify">auto</span><span style=3D"color: #000;" class=3D"styled-by-pret=
tify"> </span><span style=3D"color: #660;" class=3D"styled-by-prettify">[</=
span><span style=3D"color: #000;" class=3D"styled-by-prettify">key</span><s=
pan style=3D"color: #660;" class=3D"styled-by-prettify">,</span><span style=
=3D"color: #000;" class=3D"styled-by-prettify">value</span><span style=3D"c=
olor: #660;" class=3D"styled-by-prettify">])</span><span style=3D"color: #0=
00;" class=3D"styled-by-prettify"> </span><span style=3D"color: #660;" clas=
s=3D"styled-by-prettify">{</span><span style=3D"color: #000;" class=3D"styl=
ed-by-prettify"> </span><span style=3D"color: #660;" class=3D"styled-by-pre=
ttify">...</span><span style=3D"color: #000;" class=3D"styled-by-prettify">=
 </span><span style=3D"color: #660;" class=3D"styled-by-prettify">});</span=
><font color=3D"#666600"></font></div></code></div><br>The previous post on=
 this page was here (https://groups.google.com/a/isocpp.org/forum/?fromgrou=
ps#!searchin/std-proposals/structured$20bindings$20/std-proposals/EsPJnQooP=
oI/24Gd4PGABgAJ)</div><div><br></div><div>And a formal paper proposing the =
idea has been attached to this post.</div></div>

<p></p>

-- <br />
You received this message because you are subscribed to the Google Groups &=
quot;ISO C++ Standard - Future Proposals&quot; group.<br />
To unsubscribe from this group and stop receiving emails from it, send an e=
mail to <a href=3D"mailto:std-proposals+unsubscribe@isocpp.org">std-proposa=
ls+unsubscribe@isocpp.org</a>.<br />
To post to this group, send email to <a href=3D"mailto:std-proposals@isocpp=
..org">std-proposals@isocpp.org</a>.<br />
To view this discussion on the web visit <a href=3D"https://groups.google.c=
om/a/isocpp.org/d/msgid/std-proposals/b8d14aa1-adcb-41d9-8fe8-d70805927161%=
40isocpp.org?utm_medium=3Demail&utm_source=3Dfooter">https://groups.google.=
com/a/isocpp.org/d/msgid/std-proposals/b8d14aa1-adcb-41d9-8fe8-d70805927161=
%40isocpp.org</a>.<br />

------=_Part_2874_1944788656.1503682611453--

------=_Part_2873_1902952938.1503682611453
Content-Type: application/pdf; name=doc.pdf
Content-Transfer-Encoding: base64
Content-Disposition: attachment; filename=doc.pdf
X-Attachment-Id: eecfe359-6332-4a64-882c-25678c8c2055
Content-ID: <eecfe359-6332-4a64-882c-25678c8c2055>
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------=_Part_2873_1902952938.1503682611453--

.


Author: Nicol Bolas <jmckesson@gmail.com>
Date: Fri, 25 Aug 2017 11:30:37 -0700 (PDT)
Raw View
------=_Part_3032_763135980.1503685837332
Content-Type: multipart/alternative;
 boundary="----=_Part_3033_1057971446.1503685837333"

------=_Part_3033_1057971446.1503685837333
Content-Type: text/plain; charset="UTF-8"
Content-Transfer-Encoding: quoted-printable

On Friday, August 25, 2017 at 1:36:51 PM UTC-4, Curious wrote:
>
> The idea is to support structured bindings with polymorphic lambdas, for=
=20
> example:
>
> std::for_each(map, [](auto [key,value]) { ... });
>
> The previous post on this page was here (
> https://groups.google.com/a/isocpp.org/forum/?fromgroups#!searchin/std-pr=
oposals/structured$20bindings$20/std-proposals/EsPJnQooPoI/24Gd4PGABgAJ
> )
>

That thread isn't even a month old, and it had less than 20 posts in it.=20
Was there a reason to create another thread just because you formalized it=
=20
into a document?

And a formal paper proposing the idea has been attached to this post.
>

Your paper is inconsistent.

On the one hand, you say that exceptions "propagate from the call site".=20
But that conflicts with:

> A polymorphic lambda with a structured binding declaration translates to=
=20
a simple functor with a templated operator() method with the structured=20
binding =E2=80=9Ddecomposition=E2=80=9D happening inside the function

If the exception propagates from the call site, then it must be the call=20
site that *generates* the exception. But `get` is not called from the call=
=20
site. It is called *within* the function. Therefore, the exception must=20
propagate from some location within the function. Now obviously, it will go=
=20
through the call site to be caught.

Also, now you need to explicitly specify the *order* in which these=20
decompositions happen. That is, if you have two structured binding=20
parameters, which one gets decomposed first? At the very least, you should=
=20
explicitly state that there is no order.

Similarly, there are questions about how the accessibility of the tuple=20
machinery work:

> And as such the function template only participates in overloading when=
=20
all the structured bindings are appropriately decomposable at the call site=
..

So if the tuple machinery for a type is private, and the generation point=
=20
of that lambda can access it, and I pass it to some code that does not have=
=20
access to it, that would be il-formed? And if the generation point couldn't=
=20
access it, but the call site could access it, that would not be il-formed?

Furthermore, the question of accessibility also makes you wonder how=20
`is_decomposable` is supposed to work. If the tuple `get` is a member and=
=20
is private, is the type still decomposable? A regular structured binding=20
declaration would allow you to decompose it, but only in code that can=20
access the privates.

Either the function being called does the decomposition or it doesn't. If=
=20
the lambda performs the decomposition, then the ability to do decomposition=
=20
should be based on the static definition of the lambda (ie: where it was=20
written), exceptions should propagate from within the lambda, and the=20
conversion-to-function-pointer mechanism should be able to convert to=20
tuples.

--=20
You received this message because you are subscribed to the Google Groups "=
ISO C++ Standard - Future Proposals" group.
To unsubscribe from this group and stop receiving emails from it, send an e=
mail to std-proposals+unsubscribe@isocpp.org.
To post to this group, send email to std-proposals@isocpp.org.
To view this discussion on the web visit https://groups.google.com/a/isocpp=
..org/d/msgid/std-proposals/8497b31b-7c9d-4334-ac22-0809c958cb93%40isocpp.or=
g.

------=_Part_3033_1057971446.1503685837333
Content-Type: text/html; charset="UTF-8"
Content-Transfer-Encoding: quoted-printable

<div dir=3D"ltr">On Friday, August 25, 2017 at 1:36:51 PM UTC-4, Curious wr=
ote:<blockquote class=3D"gmail_quote" style=3D"margin: 0;margin-left: 0.8ex=
;border-left: 1px #ccc solid;padding-left: 1ex;"><div dir=3D"ltr">The idea =
is to support structured bindings with polymorphic lambdas, for example:<di=
v><br></div><div><div style=3D"background-color:rgb(250,250,250);border:1px=
 solid rgb(187,187,187);word-wrap:break-word"><code><div><span style=3D"col=
or:#000">std</span><span style=3D"color:#660">::</span><span style=3D"color=
:#000">for_each</span><span style=3D"color:#660">(</span><span style=3D"col=
or:#000">map</span><span style=3D"color:#660">,</span><span style=3D"color:=
#000"> </span><span style=3D"color:#660">[](</span><span style=3D"color:#00=
8">auto</span><span style=3D"color:#000"> </span><span style=3D"color:#660"=
>[</span><span style=3D"color:#000">key</span><span style=3D"color:#660">,<=
/span><span style=3D"color:#000">value</span><span style=3D"color:#660">])<=
/span><span style=3D"color:#000"> </span><span style=3D"color:#660">{</span=
><span style=3D"color:#000"> </span><span style=3D"color:#660">...</span><s=
pan style=3D"color:#000"> </span><span style=3D"color:#660">});</span><font=
 color=3D"#666600"></font></div></code></div><br>The previous post on this =
page was here (<a href=3D"https://groups.google.com/a/isocpp.org/forum/?fro=
mgroups#!searchin/std-proposals/structured$20bindings$20/std-proposals/EsPJ=
nQooPoI/24Gd4PGABgAJ" target=3D"_blank" rel=3D"nofollow" onmousedown=3D"thi=
s.href=3D&#39;https://groups.google.com/a/isocpp.org/forum/?fromgroups#!sea=
rchin/std-proposals/structured$20bindings$20/std-proposals/EsPJnQooPoI/24Gd=
4PGABgAJ&#39;;return true;" onclick=3D"this.href=3D&#39;https://groups.goog=
le.com/a/isocpp.org/forum/?fromgroups#!searchin/std-proposals/structured$20=
bindings$20/std-proposals/EsPJnQooPoI/24Gd4PGABgAJ&#39;;return true;">https=
://groups.google.com/a/<wbr>isocpp.org/forum/?fromgroups#!<wbr>searchin/std=
-proposals/<wbr>structured$20bindings$20/std-<wbr>proposals/EsPJnQooPoI/<wb=
r>24Gd4PGABgAJ</a>)</div></div></blockquote><div><br>That thread isn&#39;t =
even a month old, and it had less than 20 posts in it. Was there a reason t=
o create another thread just because you formalized it into a document?<br>=
<br></div><blockquote class=3D"gmail_quote" style=3D"margin: 0;margin-left:=
 0.8ex;border-left: 1px #ccc solid;padding-left: 1ex;"><div dir=3D"ltr"><di=
v></div><div>And a formal paper proposing the idea has been attached to thi=
s post.</div></div></blockquote><div><br>Your paper is inconsistent.<br><br=
>On the one hand, you say that exceptions &quot;propagate from the call sit=
e&quot;. But that conflicts with:<br><br>&gt; A polymorphic lambda with a s=
tructured binding declaration translates to a simple functor with a templat=
ed operator() method with the structured binding =E2=80=9Ddecomposition=E2=
=80=9D happening inside the function<br><br>If the exception propagates fro=
m the call site, then it must be the call site that <i>generates</i> the ex=
ception. But `get` is not called from the call site. It is called <i>within=
</i> the function. Therefore, the exception must propagate from some locati=
on within the function. Now obviously, it will go through the call site to =
be caught.<br><br>Also, now you need to explicitly specify the <i>order</i>=
 in which these decompositions happen. That is, if you have two structured =
binding parameters, which one gets decomposed first? At the very least, you=
 should explicitly state that there is no order.<br><br>Similarly, there ar=
e questions about how the accessibility of the tuple machinery work:<br><br=
>&gt; And as such the function template only participates in overloading wh=
en all the structured bindings are appropriately decomposable at the call s=
ite.<br><br>So if the tuple machinery for a type is private, and the genera=
tion point of that lambda can access it, and I pass it to some code that do=
es not have access to it, that would be il-formed? And if the generation po=
int couldn&#39;t access it, but the call site could access it, that would n=
ot be il-formed?<br><br>Furthermore, the question of accessibility also mak=
es you wonder how `is_decomposable` is supposed to work. If the tuple `get`=
 is a member and is private, is the type still decomposable? A regular stru=
ctured binding declaration would allow you to decompose it, but only in cod=
e that can access the privates.<br><br>Either the function being called doe=
s the decomposition or it doesn&#39;t. If the lambda performs the decomposi=
tion, then the ability to do decomposition should be based on the static de=
finition of the lambda (ie: where it was written), exceptions should propag=
ate from within the lambda, and the conversion-to-function-pointer mechanis=
m should be able to convert to tuples.<br></div></div>

<p></p>

-- <br />
You received this message because you are subscribed to the Google Groups &=
quot;ISO C++ Standard - Future Proposals&quot; group.<br />
To unsubscribe from this group and stop receiving emails from it, send an e=
mail to <a href=3D"mailto:std-proposals+unsubscribe@isocpp.org">std-proposa=
ls+unsubscribe@isocpp.org</a>.<br />
To post to this group, send email to <a href=3D"mailto:std-proposals@isocpp=
..org">std-proposals@isocpp.org</a>.<br />
To view this discussion on the web visit <a href=3D"https://groups.google.c=
om/a/isocpp.org/d/msgid/std-proposals/8497b31b-7c9d-4334-ac22-0809c958cb93%=
40isocpp.org?utm_medium=3Demail&utm_source=3Dfooter">https://groups.google.=
com/a/isocpp.org/d/msgid/std-proposals/8497b31b-7c9d-4334-ac22-0809c958cb93=
%40isocpp.org</a>.<br />

------=_Part_3033_1057971446.1503685837333--

------=_Part_3032_763135980.1503685837332--

.


Author: Curious <rmn100@gmail.com>
Date: Fri, 25 Aug 2017 12:19:54 -0700 (PDT)
Raw View
------=_Part_3071_826348081.1503688794608
Content-Type: multipart/alternative;
 boundary="----=_Part_3072_2146848794.1503688794608"

------=_Part_3072_2146848794.1503688794608
Content-Type: text/plain; charset="UTF-8"

This is great feedback, thanks!  I was not sure about whether I should
start a new thread or not with the proposal.  Sorry about that!

Your paper is inconsistent.
>

You are right!  I forgot to address exception handling in the translation
to the functor, I will make a note that this is another difference in how
the real "translation works".  Will do so.

Also, now you need to explicitly specify the *order* in which these
> decompositions happen. That is, if you have two structured binding
> parameters, which one gets decomposed first? At the very least, you should
> explicitly state that there is no order.
>

 In my mind they should follow the same order as for a regular function,
with the decompositions happening in the same order as constructions of the
parameters.

So if the tuple machinery for a type is private, and the generation point
> of that lambda can access it, and I pass it to some code that does not have
> access to it, that would be il-formed? And if the generation point couldn't
> access it, but the call site could access it, that would not be il-formed?
>

Right, I would say the private get<>() function should be considered by the
compiler intrinsic, and if a type has a private get<>() then it is still
decomposable,  the private issue will be flagged by the compiler just as if
the decomposition had happened inside the lambda.  What do you think should
happen here?

Thanks for the suggestions, these are great points!  I will address them in
the next version of the paper :)

--
You received this message because you are subscribed to the Google Groups "ISO C++ Standard - Future Proposals" group.
To unsubscribe from this group and stop receiving emails from it, send an email to std-proposals+unsubscribe@isocpp.org.
To post to this group, send email to std-proposals@isocpp.org.
To view this discussion on the web visit https://groups.google.com/a/isocpp.org/d/msgid/std-proposals/15a70d94-e039-4f82-ba01-bde9d3fbacbd%40isocpp.org.

------=_Part_3072_2146848794.1503688794608
Content-Type: text/html; charset="UTF-8"
Content-Transfer-Encoding: quoted-printable

<div dir=3D"ltr">This is great feedback, thanks! =C2=A0I was not sure about=
 whether I should start a new thread or not with the proposal. =C2=A0Sorry =
about that!<br><br><blockquote class=3D"gmail_quote" style=3D"margin: 0;mar=
gin-left: 0.8ex;border-left: 1px #ccc solid;padding-left: 1ex;"><div dir=3D=
"ltr"><div>Your paper is inconsistent.<br></div></div></blockquote><div><br=
></div><div>You are right! =C2=A0I forgot to address exception handling in =
the translation to the functor, I will make a note that this is another dif=
ference in how the real &quot;translation works&quot;. =C2=A0Will do so.=C2=
=A0</div><div><br></div><blockquote class=3D"gmail_quote" style=3D"margin: =
0;margin-left: 0.8ex;border-left: 1px #ccc solid;padding-left: 1ex;"><div d=
ir=3D"ltr"><div>Also, now you need to explicitly specify the <i>order</i> i=
n which these decompositions happen. That is, if you have two structured bi=
nding parameters, which one gets decomposed first? At the very least, you s=
hould explicitly state that there is no order.<br></div></div></blockquote>=
<div><br></div><div>=C2=A0In my mind they should follow the same order as f=
or a regular function, with the decompositions happening in the same order =
as constructions of the parameters. =C2=A0</div><div><br></div><blockquote =
class=3D"gmail_quote" style=3D"margin: 0;margin-left: 0.8ex;border-left: 1p=
x #ccc solid;padding-left: 1ex;"><div dir=3D"ltr"><div>So if the tuple mach=
inery for a type is private, and the generation point of that lambda can ac=
cess it, and I pass it to some code that does not have access to it, that w=
ould be il-formed? And if the generation point couldn&#39;t access it, but =
the call site could access it, that would not be il-formed?<br></div></div>=
</blockquote><div>=C2=A0</div><div>Right, I would say the private <font fac=
e=3D"courier new, monospace">get&lt;&gt;()</font> function should be consid=
ered by the compiler intrinsic, and if a type has a private <font face=3D"c=
ourier new, monospace">get&lt;&gt;()</font> then it is still decomposable, =
=C2=A0the private issue will be flagged by the compiler just as if the deco=
mposition had happened inside the lambda. =C2=A0What do you think should ha=
ppen here?</div><div>=C2=A0</div><div>Thanks for the suggestions, these are=
 great points! =C2=A0I will address them in the next version of the paper :=
)=C2=A0</div></div>

<p></p>

-- <br />
You received this message because you are subscribed to the Google Groups &=
quot;ISO C++ Standard - Future Proposals&quot; group.<br />
To unsubscribe from this group and stop receiving emails from it, send an e=
mail to <a href=3D"mailto:std-proposals+unsubscribe@isocpp.org">std-proposa=
ls+unsubscribe@isocpp.org</a>.<br />
To post to this group, send email to <a href=3D"mailto:std-proposals@isocpp=
..org">std-proposals@isocpp.org</a>.<br />
To view this discussion on the web visit <a href=3D"https://groups.google.c=
om/a/isocpp.org/d/msgid/std-proposals/15a70d94-e039-4f82-ba01-bde9d3fbacbd%=
40isocpp.org?utm_medium=3Demail&utm_source=3Dfooter">https://groups.google.=
com/a/isocpp.org/d/msgid/std-proposals/15a70d94-e039-4f82-ba01-bde9d3fbacbd=
%40isocpp.org</a>.<br />

------=_Part_3072_2146848794.1503688794608--

------=_Part_3071_826348081.1503688794608--

.


Author: Curious <rmn100@gmail.com>
Date: Fri, 25 Aug 2017 21:26:38 -0700 (PDT)
Raw View
------=_Part_3686_1047053551.1503721598826
Content-Type: multipart/alternative;
 boundary="----=_Part_3687_947339202.1503721598826"

------=_Part_3687_947339202.1503721598826
Content-Type: text/plain; charset="UTF-8"

Here is the updated paper with several important changes.

   1. Exception propagation semantics have been addressed
   2. Reference-ness of the bindings has been addressed, this has important
   consequences with determining which version of get<>() is called
   3. Multiple decomposition order has been addressed
   4. A member access clarification during the decomposition process has
   been added.  With a code example.
   5. Wording changes


On Friday, 25 August 2017 12:19:54 UTC-7, Curious wrote:
>
> This is great feedback, thanks!  I was not sure about whether I should
> start a new thread or not with the proposal.  Sorry about that!
>
> Your paper is inconsistent.
>>
>
> You are right!  I forgot to address exception handling in the translation
> to the functor, I will make a note that this is another difference in how
> the real "translation works".  Will do so.
>
> Also, now you need to explicitly specify the *order* in which these
>> decompositions happen. That is, if you have two structured binding
>> parameters, which one gets decomposed first? At the very least, you should
>> explicitly state that there is no order.
>>
>
>  In my mind they should follow the same order as for a regular function,
> with the decompositions happening in the same order as constructions of the
> parameters.
>
> So if the tuple machinery for a type is private, and the generation point
>> of that lambda can access it, and I pass it to some code that does not have
>> access to it, that would be il-formed? And if the generation point couldn't
>> access it, but the call site could access it, that would not be il-formed?
>>
>
> Right, I would say the private get<>() function should be considered by
> the compiler intrinsic, and if a type has a private get<>() then it is
> still decomposable,  the private issue will be flagged by the compiler just
> as if the decomposition had happened inside the lambda.  What do you think
> should happen here?
>
> Thanks for the suggestions, these are great points!  I will address them
> in the next version of the paper :)
>

--
You received this message because you are subscribed to the Google Groups "ISO C++ Standard - Future Proposals" group.
To unsubscribe from this group and stop receiving emails from it, send an email to std-proposals+unsubscribe@isocpp.org.
To post to this group, send email to std-proposals@isocpp.org.
To view this discussion on the web visit https://groups.google.com/a/isocpp.org/d/msgid/std-proposals/6b50933d-291b-4b47-8c0c-82c97d9cb406%40isocpp.org.

------=_Part_3687_947339202.1503721598826
Content-Type: text/html; charset="UTF-8"
Content-Transfer-Encoding: quoted-printable

<div dir=3D"ltr">Here is the updated paper with several important changes. =
=C2=A0<div><ol><li>Exception propagation semantics have been addressed</li>=
<li>Reference-ness of the bindings has been addressed, this has important c=
onsequences with determining which version of <font face=3D"courier new, mo=
nospace">get&lt;&gt;()</font> is called</li><li>Multiple decomposition orde=
r has been addressed</li><li>A member access clarification during the decom=
position process has been added. =C2=A0With a code example.</li><li>Wording=
 changes</li></ol><br>On Friday, 25 August 2017 12:19:54 UTC-7, Curious  wr=
ote:<blockquote class=3D"gmail_quote" style=3D"margin: 0;margin-left: 0.8ex=
;border-left: 1px #ccc solid;padding-left: 1ex;"><div dir=3D"ltr">This is g=
reat feedback, thanks! =C2=A0I was not sure about whether I should start a =
new thread or not with the proposal. =C2=A0Sorry about that!<br><br><blockq=
uote class=3D"gmail_quote" style=3D"margin:0;margin-left:0.8ex;border-left:=
1px #ccc solid;padding-left:1ex"><div dir=3D"ltr"><div>Your paper is incons=
istent.<br></div></div></blockquote><div><br></div><div>You are right! =C2=
=A0I forgot to address exception handling in the translation to the functor=
, I will make a note that this is another difference in how the real &quot;=
translation works&quot;. =C2=A0Will do so.=C2=A0</div><div><br></div><block=
quote class=3D"gmail_quote" style=3D"margin:0;margin-left:0.8ex;border-left=
:1px #ccc solid;padding-left:1ex"><div dir=3D"ltr"><div>Also, now you need =
to explicitly specify the <i>order</i> in which these decompositions happen=
.. That is, if you have two structured binding parameters, which one gets de=
composed first? At the very least, you should explicitly state that there i=
s no order.<br></div></div></blockquote><div><br></div><div>=C2=A0In my min=
d they should follow the same order as for a regular function, with the dec=
ompositions happening in the same order as constructions of the parameters.=
 =C2=A0</div><div><br></div><blockquote class=3D"gmail_quote" style=3D"marg=
in:0;margin-left:0.8ex;border-left:1px #ccc solid;padding-left:1ex"><div di=
r=3D"ltr"><div>So if the tuple machinery for a type is private, and the gen=
eration point of that lambda can access it, and I pass it to some code that=
 does not have access to it, that would be il-formed? And if the generation=
 point couldn&#39;t access it, but the call site could access it, that woul=
d not be il-formed?<br></div></div></blockquote><div>=C2=A0</div><div>Right=
, I would say the private <font face=3D"courier new, monospace">get&lt;&gt;=
()</font> function should be considered by the compiler intrinsic, and if a=
 type has a private <font face=3D"courier new, monospace">get&lt;&gt;()</fo=
nt> then it is still decomposable, =C2=A0the private issue will be flagged =
by the compiler just as if the decomposition had happened inside the lambda=
.. =C2=A0What do you think should happen here?</div><div>=C2=A0</div><div>Th=
anks for the suggestions, these are great points! =C2=A0I will address them=
 in the next version of the paper :)=C2=A0</div></div></blockquote></div></=
div>

<p></p>

-- <br />
You received this message because you are subscribed to the Google Groups &=
quot;ISO C++ Standard - Future Proposals&quot; group.<br />
To unsubscribe from this group and stop receiving emails from it, send an e=
mail to <a href=3D"mailto:std-proposals+unsubscribe@isocpp.org">std-proposa=
ls+unsubscribe@isocpp.org</a>.<br />
To post to this group, send email to <a href=3D"mailto:std-proposals@isocpp=
..org">std-proposals@isocpp.org</a>.<br />
To view this discussion on the web visit <a href=3D"https://groups.google.c=
om/a/isocpp.org/d/msgid/std-proposals/6b50933d-291b-4b47-8c0c-82c97d9cb406%=
40isocpp.org?utm_medium=3Demail&utm_source=3Dfooter">https://groups.google.=
com/a/isocpp.org/d/msgid/std-proposals/6b50933d-291b-4b47-8c0c-82c97d9cb406=
%40isocpp.org</a>.<br />

------=_Part_3687_947339202.1503721598826--

------=_Part_3686_1047053551.1503721598826
Content-Type: application/pdf; name=doc.pdf
Content-Transfer-Encoding: base64
Content-Disposition: attachment; filename=doc.pdf
X-Attachment-Id: 4d6bad8f-a736-4a64-9431-78c77fe69da9
Content-ID: <4d6bad8f-a736-4a64-9431-78c77fe69da9>
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------=_Part_3686_1047053551.1503721598826--

.


Author: Zhihao Yuan <zy@miator.net>
Date: Sat, 26 Aug 2017 16:07:27 -0500
Raw View
On Fri, Aug 25, 2017 at 2:19 PM, Curious <rmn100@gmail.com> wrote:
>
>> Also, now you need to explicitly specify the order in which these
>> decompositions happen. That is, if you have two structured binding
>> parameters, which one gets decomposed first? At the very least, you should
>> explicitly state that there is no order.
>
>  In my mind they should follow the same order as for a regular function,
> with the decompositions happening in the same order as constructions of the
> parameters.
>

In your latest draft, you choose to decompose inside
function body, so I have a further suggestion: entirely
split the decomposition step from the parameter
copy-init step and define the decomposition order
to be left-to-right.

  [] (auto [a, b] /* underlying object x */,
      auto [c, d] /* underlying object y */) {...}

When invoking this function, copy-init x and y in
unspecific order, then decompose x into a and b,
then decompose y into c and d.  This can further
simplify the model, because that will be no difference
from

  [] (auto x, auto y) {...}

from the caller's point of view.

--
Zhihao Yuan, ID lichray
The best way to predict the future is to invent it.
_______________________________________________

--
You received this message because you are subscribed to the Google Groups "ISO C++ Standard - Future Proposals" group.
To unsubscribe from this group and stop receiving emails from it, send an email to std-proposals+unsubscribe@isocpp.org.
To post to this group, send email to std-proposals@isocpp.org.
To view this discussion on the web visit https://groups.google.com/a/isocpp.org/d/msgid/std-proposals/CAGsORuDZ%3DTVXNXr5NfZv-fry_kCRkmp_0%2BkNy59EqoRgr_BzPg%40mail.gmail.com.

.


Author: Curious <rmn100@gmail.com>
Date: Sat, 26 Aug 2017 14:54:48 -0700 (PDT)
Raw View
------=_Part_4823_1053186380.1503784489073
Content-Type: multipart/alternative;
 boundary="----=_Part_4824_639189993.1503784489073"

------=_Part_4824_639189993.1503784489073
Content-Type: text/plain; charset="UTF-8"

Yeah I intentionally defined it like that.  In the expansion of the lambda
the copy-init (if any) happens before the decomposition; the actual
decomposition step happens inside the body of the function.  This also fits
the scope visibility issue that I mentioned.  Did I leave something
specified ambiguously?

On Saturday, 26 August 2017 14:07:31 UTC-7, Zhihao Yuan wrote:
>
> On Fri, Aug 25, 2017 at 2:19 PM, Curious <rmn...@gmail.com <javascript:>>
> wrote:
> >
> >> Also, now you need to explicitly specify the order in which these
> >> decompositions happen. That is, if you have two structured binding
> >> parameters, which one gets decomposed first? At the very least, you
> should
> >> explicitly state that there is no order.
> >
> >  In my mind they should follow the same order as for a regular function,
> > with the decompositions happening in the same order as constructions of
> the
> > parameters.
> >
>
> In your latest draft, you choose to decompose inside
> function body, so I have a further suggestion: entirely
> split the decomposition step from the parameter
> copy-init step and define the decomposition order
> to be left-to-right.
>
>   [] (auto [a, b] /* underlying object x */,
>       auto [c, d] /* underlying object y */) {...}
>
> When invoking this function, copy-init x and y in
> unspecific order, then decompose x into a and b,
> then decompose y into c and d.  This can further
> simplify the model, because that will be no difference
> from
>
>   [] (auto x, auto y) {...}
>
> from the caller's point of view.
>
> --
> Zhihao Yuan, ID lichray
> The best way to predict the future is to invent it.
> _______________________________________________
>

--
You received this message because you are subscribed to the Google Groups "ISO C++ Standard - Future Proposals" group.
To unsubscribe from this group and stop receiving emails from it, send an email to std-proposals+unsubscribe@isocpp.org.
To post to this group, send email to std-proposals@isocpp.org.
To view this discussion on the web visit https://groups.google.com/a/isocpp.org/d/msgid/std-proposals/f0a5b11a-7fb8-4243-a8c2-51a6aaaaf1d5%40isocpp.org.

------=_Part_4824_639189993.1503784489073
Content-Type: text/html; charset="UTF-8"
Content-Transfer-Encoding: quoted-printable

<div dir=3D"ltr">Yeah I intentionally defined it like that. =C2=A0In the ex=
pansion of the lambda the copy-init (if any) happens before the decompositi=
on; the actual decomposition step happens inside the body of the function. =
=C2=A0This also fits the scope visibility issue that I mentioned. =C2=A0Did=
 I leave something specified ambiguously?<div><br>On Saturday, 26 August 20=
17 14:07:31 UTC-7, Zhihao Yuan  wrote:<blockquote class=3D"gmail_quote" sty=
le=3D"margin: 0;margin-left: 0.8ex;border-left: 1px #ccc solid;padding-left=
: 1ex;">On Fri, Aug 25, 2017 at 2:19 PM, Curious &lt;<a href=3D"javascript:=
" target=3D"_blank" gdf-obfuscated-mailto=3D"qC4mgfQNDAAJ" rel=3D"nofollow"=
 onmousedown=3D"this.href=3D&#39;javascript:&#39;;return true;" onclick=3D"=
this.href=3D&#39;javascript:&#39;;return true;">rmn...@gmail.com</a>&gt; wr=
ote:
<br>&gt;
<br>&gt;&gt; Also, now you need to explicitly specify the order in which th=
ese
<br>&gt;&gt; decompositions happen. That is, if you have two structured bin=
ding
<br>&gt;&gt; parameters, which one gets decomposed first? At the very least=
, you should
<br>&gt;&gt; explicitly state that there is no order.
<br>&gt;
<br>&gt; =C2=A0In my mind they should follow the same order as for a regula=
r function,
<br>&gt; with the decompositions happening in the same order as constructio=
ns of the
<br>&gt; parameters.
<br>&gt;
<br>
<br>In your latest draft, you choose to decompose inside
<br>function body, so I have a further suggestion: entirely
<br>split the decomposition step from the parameter
<br>copy-init step and define the decomposition order
<br>to be left-to-right.
<br>
<br>=C2=A0 [] (auto [a, b] /* underlying object x */,
<br>=C2=A0 =C2=A0 =C2=A0 auto [c, d] /* underlying object y */) {...}
<br>
<br>When invoking this function, copy-init x and y in
<br>unspecific order, then decompose x into a and b,
<br>then decompose y into c and d. =C2=A0This can further
<br>simplify the model, because that will be no difference
<br>from
<br>
<br>=C2=A0 [] (auto x, auto y) {...}
<br>
<br>from the caller&#39;s point of view.
<br>
<br>--=20
<br>Zhihao Yuan, ID lichray
<br>The best way to predict the future is to invent it.
<br>______________________________<wbr>_________________
<br></blockquote></div></div>

<p></p>

-- <br />
You received this message because you are subscribed to the Google Groups &=
quot;ISO C++ Standard - Future Proposals&quot; group.<br />
To unsubscribe from this group and stop receiving emails from it, send an e=
mail to <a href=3D"mailto:std-proposals+unsubscribe@isocpp.org">std-proposa=
ls+unsubscribe@isocpp.org</a>.<br />
To post to this group, send email to <a href=3D"mailto:std-proposals@isocpp=
..org">std-proposals@isocpp.org</a>.<br />
To view this discussion on the web visit <a href=3D"https://groups.google.c=
om/a/isocpp.org/d/msgid/std-proposals/f0a5b11a-7fb8-4243-a8c2-51a6aaaaf1d5%=
40isocpp.org?utm_medium=3Demail&utm_source=3Dfooter">https://groups.google.=
com/a/isocpp.org/d/msgid/std-proposals/f0a5b11a-7fb8-4243-a8c2-51a6aaaaf1d5=
%40isocpp.org</a>.<br />

------=_Part_4824_639189993.1503784489073--

------=_Part_4823_1053186380.1503784489073--

.


Author: Zhihao Yuan <zy@miator.net>
Date: Sat, 26 Aug 2017 19:51:31 -0500
Raw View
On Sat, Aug 26, 2017 at 4:54 PM, Curious <rmn100@gmail.com> wrote:
> Yeah I intentionally defined it like that.  In the expansion of the lambda
> the copy-init (if any) happens before the decomposition; the actual
> decomposition step happens inside the body of the function.  This also fits
> the scope visibility issue that I mentioned.  Did I leave something
> specified ambiguously?
>

Hmmm, no.  I just didn't see this discussion in
section 7, which briefly introduced the model
again.  Maybe put section 7 in section 5.2?

--
Zhihao Yuan, ID lichray
The best way to predict the future is to invent it.
_______________________________________________

--
You received this message because you are subscribed to the Google Groups "ISO C++ Standard - Future Proposals" group.
To unsubscribe from this group and stop receiving emails from it, send an email to std-proposals+unsubscribe@isocpp.org.
To post to this group, send email to std-proposals@isocpp.org.
To view this discussion on the web visit https://groups.google.com/a/isocpp.org/d/msgid/std-proposals/CAGsORuBeCYWv-a5LiTkQAQFV39W3HgYPC3Y263ucvGioyb%3Dy7g%40mail.gmail.com.

.


Author: Curious <rmn100@gmail.com>
Date: Sat, 26 Aug 2017 20:07:21 -0700 (PDT)
Raw View
------=_Part_2336_638079184.1503803241981
Content-Type: multipart/alternative;
 boundary="----=_Part_2337_986604082.1503803241981"

------=_Part_2337_986604082.1503803241981
Content-Type: text/plain; charset="UTF-8"

The reason I didn't specify the details in section 7 again in section 5 was
because the latter introduced the idea of the expansion and that already
has the effect that the decompositions are done inside the lambda.  Would
you still recommend I merge sections 7 and 5?

On Saturday, 26 August 2017 17:51:35 UTC-7, Zhihao Yuan wrote:
>
> On Sat, Aug 26, 2017 at 4:54 PM, Curious <rmn...@gmail.com <javascript:>>
> wrote:
> > Yeah I intentionally defined it like that.  In the expansion of the
> lambda
> > the copy-init (if any) happens before the decomposition; the actual
> > decomposition step happens inside the body of the function.  This also
> fits
> > the scope visibility issue that I mentioned.  Did I leave something
> > specified ambiguously?
> >
>
> Hmmm, no.  I just didn't see this discussion in
> section 7, which briefly introduced the model
> again.  Maybe put section 7 in section 5.2?
>
> --
> Zhihao Yuan, ID lichray
> The best way to predict the future is to invent it.
> _______________________________________________
>

--
You received this message because you are subscribed to the Google Groups "ISO C++ Standard - Future Proposals" group.
To unsubscribe from this group and stop receiving emails from it, send an email to std-proposals+unsubscribe@isocpp.org.
To post to this group, send email to std-proposals@isocpp.org.
To view this discussion on the web visit https://groups.google.com/a/isocpp.org/d/msgid/std-proposals/47be56a4-eb5b-41b5-a4fd-039ee44583f7%40isocpp.org.

------=_Part_2337_986604082.1503803241981
Content-Type: text/html; charset="UTF-8"
Content-Transfer-Encoding: quoted-printable

<div dir=3D"ltr">The reason I didn&#39;t specify the details in section 7 a=
gain in section 5 was because the latter introduced the idea of the expansi=
on and that already has the effect that the decompositions are done inside =
the lambda. =C2=A0Would you still recommend I merge sections 7 and 5? =C2=
=A0<br><br>On Saturday, 26 August 2017 17:51:35 UTC-7, Zhihao Yuan  wrote:<=
blockquote class=3D"gmail_quote" style=3D"margin: 0;margin-left: 0.8ex;bord=
er-left: 1px #ccc solid;padding-left: 1ex;">On Sat, Aug 26, 2017 at 4:54 PM=
, Curious &lt;<a href=3D"javascript:" target=3D"_blank" gdf-obfuscated-mail=
to=3D"L0gl4y4aDAAJ" rel=3D"nofollow" onmousedown=3D"this.href=3D&#39;javasc=
ript:&#39;;return true;" onclick=3D"this.href=3D&#39;javascript:&#39;;retur=
n true;">rmn...@gmail.com</a>&gt; wrote:
<br>&gt; Yeah I intentionally defined it like that. =C2=A0In the expansion =
of the lambda
<br>&gt; the copy-init (if any) happens before the decomposition; the actua=
l
<br>&gt; decomposition step happens inside the body of the function. =C2=A0=
This also fits
<br>&gt; the scope visibility issue that I mentioned. =C2=A0Did I leave som=
ething
<br>&gt; specified ambiguously?
<br>&gt;
<br>
<br>Hmmm, no. =C2=A0I just didn&#39;t see this discussion in
<br>section 7, which briefly introduced the model
<br>again. =C2=A0Maybe put section 7 in section 5.2?
<br>
<br>--=20
<br>Zhihao Yuan, ID lichray
<br>The best way to predict the future is to invent it.
<br>______________________________<wbr>_________________
<br></blockquote></div>

<p></p>

-- <br />
You received this message because you are subscribed to the Google Groups &=
quot;ISO C++ Standard - Future Proposals&quot; group.<br />
To unsubscribe from this group and stop receiving emails from it, send an e=
mail to <a href=3D"mailto:std-proposals+unsubscribe@isocpp.org">std-proposa=
ls+unsubscribe@isocpp.org</a>.<br />
To post to this group, send email to <a href=3D"mailto:std-proposals@isocpp=
..org">std-proposals@isocpp.org</a>.<br />
To view this discussion on the web visit <a href=3D"https://groups.google.c=
om/a/isocpp.org/d/msgid/std-proposals/47be56a4-eb5b-41b5-a4fd-039ee44583f7%=
40isocpp.org?utm_medium=3Demail&utm_source=3Dfooter">https://groups.google.=
com/a/isocpp.org/d/msgid/std-proposals/47be56a4-eb5b-41b5-a4fd-039ee44583f7=
%40isocpp.org</a>.<br />

------=_Part_2337_986604082.1503803241981--

------=_Part_2336_638079184.1503803241981--

.


Author: Zhihao Yuan <zy@miator.net>
Date: Sun, 27 Aug 2017 00:46:29 -0500
Raw View
On Sat, Aug 26, 2017 at 10:07 PM, Curious <rmn100@gmail.com> wrote:
> The reason I didn't specify the details in section 7 again in section 5 was
> because the latter introduced the idea of the expansion and that already has
> the effect that the decompositions are done inside the lambda.  Would you
> still recommend I merge sections 7 and 5?
>

The content of section 7 is implied by 5.2, so I feel that
its importance doesn't require a full section.  Up to you;
no technical difference.

--
Zhihao Yuan, ID lichray
The best way to predict the future is to invent it.
_______________________________________________

--
You received this message because you are subscribed to the Google Groups "ISO C++ Standard - Future Proposals" group.
To unsubscribe from this group and stop receiving emails from it, send an email to std-proposals+unsubscribe@isocpp.org.
To post to this group, send email to std-proposals@isocpp.org.
To view this discussion on the web visit https://groups.google.com/a/isocpp.org/d/msgid/std-proposals/CAGsORuD1UJgXV_MdjZxQLTCr9RLsP0%2BNmxA%3Dy5YY%3DMpLy9L_OA%40mail.gmail.com.

.


Author: "T. C." <rs2740@gmail.com>
Date: Sat, 26 Aug 2017 23:09:16 -0700 (PDT)
Raw View
------=_Part_5185_980696889.1503814157012
Content-Type: multipart/alternative;
 boundary="----=_Part_5186_1301940407.1503814157012"

------=_Part_5186_1301940407.1503814157012
Content-Type: text/plain; charset="UTF-8"

How do you handle a class that is 1-decomposable at one point in the
program and 3-decomposable at another? (This can happen if you have an
intervening tuple_size etc. specialization.) And this means that the trait
is prone to ODR violations, which is an argument against providing it.

To what extent does x-decomposable check for errors? In particular, how far
do you go in checking before you call a type (not) "decomposable"? I assume
that if a get<>() instantiation would trigger a hard error, the type would
still be considered "decomposable". What about a broken tuple_size
specialization (which motivated GB 20)? A missing or broken tuple_element
specialization? A missing get? A deleted get<> overload?

Should the trait and overload resolution do the same check, or should
overload resolution do a different check? For example, while overload
resolution generally ignores access controls and deleted definitions,
traits generally do not.

The standard uses ref-qualifier for the &/&&. I hated that, which is why
cppreference doesn't use that name, but if you are writing a paper to
change the standard then you should use the name in the standard.

--
You received this message because you are subscribed to the Google Groups "ISO C++ Standard - Future Proposals" group.
To unsubscribe from this group and stop receiving emails from it, send an email to std-proposals+unsubscribe@isocpp.org.
To post to this group, send email to std-proposals@isocpp.org.
To view this discussion on the web visit https://groups.google.com/a/isocpp.org/d/msgid/std-proposals/348b59eb-c288-482e-a7f4-473d8f1fbfea%40isocpp.org.

------=_Part_5186_1301940407.1503814157012
Content-Type: text/html; charset="UTF-8"
Content-Transfer-Encoding: quoted-printable

<div dir=3D"ltr"><div>How do you handle a class that is 1-decomposable at o=
ne point in the program and 3-decomposable at another? (This can happen if =
you have an intervening tuple_size etc. specialization.) And this means tha=
t the trait is prone to ODR violations, which is an argument against provid=
ing it.</div><div><br></div><div>To what extent does x-decomposable check f=
or errors? In particular, how far do you go in checking before you call a t=
ype (not) &quot;decomposable&quot;? I assume that if a get&lt;&gt;() instan=
tiation would trigger a hard error, the type would still be considered &quo=
t;decomposable&quot;. What about a broken tuple_size specialization (which =
motivated GB 20)? A missing or broken tuple_element specialization? A missi=
ng get? A deleted get&lt;&gt; overload?=C2=A0</div><div><br></div><div>Shou=
ld the trait and overload resolution do the same check, or should overload =
resolution do a different check? For example, while overload resolution gen=
erally ignores access controls and deleted definitions, traits generally do=
 not.=C2=A0</div><div><br></div><div>The standard uses ref-qualifier for th=
e &amp;/&amp;&amp;. I hated that, which is why cppreference doesn&#39;t use=
 that name, but if you are writing a paper to change the standard then you =
should use the name in the standard.<div><br></div></div></div>

<p></p>

-- <br />
You received this message because you are subscribed to the Google Groups &=
quot;ISO C++ Standard - Future Proposals&quot; group.<br />
To unsubscribe from this group and stop receiving emails from it, send an e=
mail to <a href=3D"mailto:std-proposals+unsubscribe@isocpp.org">std-proposa=
ls+unsubscribe@isocpp.org</a>.<br />
To post to this group, send email to <a href=3D"mailto:std-proposals@isocpp=
..org">std-proposals@isocpp.org</a>.<br />
To view this discussion on the web visit <a href=3D"https://groups.google.c=
om/a/isocpp.org/d/msgid/std-proposals/348b59eb-c288-482e-a7f4-473d8f1fbfea%=
40isocpp.org?utm_medium=3Demail&utm_source=3Dfooter">https://groups.google.=
com/a/isocpp.org/d/msgid/std-proposals/348b59eb-c288-482e-a7f4-473d8f1fbfea=
%40isocpp.org</a>.<br />

------=_Part_5186_1301940407.1503814157012--

------=_Part_5185_980696889.1503814157012--

.


Author: Curious <rmn100@gmail.com>
Date: Sun, 27 Aug 2017 23:28:57 -0700 (PDT)
Raw View
------=_Part_6196_1851396653.1503901738032
Content-Type: multipart/alternative;
 boundary="----=_Part_6197_1652353992.1503901738032"

------=_Part_6197_1652353992.1503901738032
Content-Type: text/plain; charset="UTF-8"

(Replies below; not in the order you had initially posted)

To what extent does x-decomposable check for errors? In particular, how far
> do you go in checking before you call a type (not) "decomposable"? I assume
> that if a get<>() instantiation would trigger a hard error, the type would
> still be considered "decomposable". What about a broken tuple_size
> specialization (which motivated GB 20)? A missing or broken tuple_element
> specialization? A missing get? A deleted get<> overload?
>

The regular structured bindings decomposition process looks for (in order)
1. whether the type is an array type and can be decomposed into x bindings,
2. if the type has a tuple_size<> defined equal to x (the number of
bindings) 3. if the x bindings can bind to the x public data members of the
type.

Now that I think about it, is_decomposable<x> should be doing the same
thing.  And not going so far as to check if the type is decomposable into x
bindings by considering the least restrictive scope access.  When there is
a scope error that will be flagged by the compiler as a hard error (such as
when get<>() is a private member and is not accessible in the context of
the lambda).  Similarly, when there is no tuple_element<> definition to
match every x binding for the type the compiler will report a hard error.
 In both these situations is_decomposable<x> will still return true.

How do you handle a class that is 1-decomposable at one point in the
> program and 3-decomposable at another? (This can happen if you have an
> intervening tuple_size etc. specialization.) And this means that the trait
> is prone to ODR violations, which is an argument against providing it.
>

With the change I have outlined above, checking for an incomplete type
seems worrisome, yes.  For example, the following trait is prone to ODR
violations when used across translation units

template <typename IncompleteType, typename = std::enable_if_t<true>>
struct DetermineComplete {
    static constexpr const bool value = false;
};

template <typename IncompleteType>
struct DetermineComplete<
        IncompleteType,
        std::enable_if_t<sizeof(IncompleteType) == sizeof(IncompleteType)>>
{
    static constexpr const bool value = true;
};

But when you inject the above trait in an anonymous namespace, that problem
seems to be mitigated?  Perhaps then, the solution should be to inject the
trait in an anonymous namespace in the <type_traits> header?  This way, it
will be harder to violate ODR across translation units.  And if this is
used only with structured-binding-lambdas then it can either cause an
instantiation or not,  I cannot picture it causing two conflicting
instantiations across translation units.  Maybe it should be kept private
to the implementation?

Should the trait and overload resolution do the same check, or should
> overload resolution do a different check? For example, while overload
> resolution generally ignores access controls and deleted definitions,
> traits generally do not.
>

I feel like the trait should do the following checks now:

   1. If the type is an array type of cardinality x, it is x-decomposable
   2. If tuple_size<T> is a complete type for T, and tuple_size<T>::value
   is equal to x, then the type T is x-decomposable
   3. If the type is decomposable into x bindings via binding to it's x
   public data members, it is x-decomposable (referencing the same conditions
   as those for regular structured binding decompositions)

This keeps the definition simple and the semantics consistent.

The standard uses ref-qualifier for the &/&&. I hated that, which is why
> cppreference doesn't use that name, but if you are writing a paper to
> change the standard then you should use the name in the standard.
>

Thanks!  I'll make that change in the next version of the paper along with
the change related to the decomposable trait and concept.

--
You received this message because you are subscribed to the Google Groups "ISO C++ Standard - Future Proposals" group.
To unsubscribe from this group and stop receiving emails from it, send an email to std-proposals+unsubscribe@isocpp.org.
To post to this group, send email to std-proposals@isocpp.org.
To view this discussion on the web visit https://groups.google.com/a/isocpp.org/d/msgid/std-proposals/029d244a-cc53-40de-9c2f-59b1bc776c1b%40isocpp.org.

------=_Part_6197_1652353992.1503901738032
Content-Type: text/html; charset="UTF-8"
Content-Transfer-Encoding: quoted-printable

<div dir=3D"ltr"><div>(Replies below; not in the order you had initially po=
sted)</div><br><blockquote class=3D"gmail_quote" style=3D"margin: 0;margin-=
left: 0.8ex;border-left: 1px #ccc solid;padding-left: 1ex;"><div dir=3D"ltr=
"><div>To what extent does x-decomposable check for errors? In particular, =
how far do you go in checking before you call a type (not) &quot;decomposab=
le&quot;? I assume that if a get&lt;&gt;() instantiation would trigger a ha=
rd error, the type would still be considered &quot;decomposable&quot;. What=
 about a broken tuple_size specialization (which motivated GB 20)? A missin=
g or broken tuple_element specialization? A missing get? A deleted get&lt;&=
gt; overload?=C2=A0</div></div></blockquote><div><br></div><div>The regular=
 structured bindings decomposition process looks for (in order) 1. whether =
the type is an array type and can be decomposed into x bindings, 2. if the =
type has a <font face=3D"courier new, monospace">tuple_size&lt;&gt;</font> =
defined equal to <font face=3D"courier new, monospace">x</font> (the number=
 of bindings) 3. if the <font face=3D"courier new, monospace">x</font> bind=
ings can bind to the <font face=3D"courier new, monospace">x</font> public =
data members of the type. =C2=A0</div><div><br></div><div>Now that I think =
about it, <font face=3D"courier new, monospace">is_decomposable&lt;x&gt;</f=
ont> should be doing the same thing. =C2=A0And not going so far as to check=
 if the type is decomposable into <font face=3D"courier new, monospace">x</=
font> bindings by considering the least restrictive scope access. =C2=A0Whe=
n there is a scope error that will be flagged by the compiler as a hard err=
or (such as when <font face=3D"courier new, monospace">get&lt;&gt;()</font>=
 is a private member and is not accessible in the context of the lambda). =
=C2=A0Similarly, when there is no <font face=3D"courier new, monospace">tup=
le_element&lt;&gt;</font> definition to match every <font face=3D"courier n=
ew, monospace">x</font> binding for the type the compiler will report a har=
d error. =C2=A0In both these situations <font face=3D"courier new, monospac=
e">is_decomposable&lt;x&gt;</font> will still return true.</div><div><br></=
div><div><blockquote class=3D"gmail_quote" style=3D"margin: 0px 0px 0px 0.8=
ex; border-left-width: 1px; border-left-style: solid; border-left-color: rg=
b(204, 204, 204); padding-left: 1ex;"><div dir=3D"ltr">How do you handle a =
class that is 1-decomposable at one point in the program and 3-decomposable=
 at another? (This can happen if you have an intervening tuple_size etc. sp=
ecialization.) And this means that the trait is prone to ODR violations, wh=
ich is an argument against providing it.</div></blockquote><div><br></div><=
div>With the change I have outlined above, checking for an incomplete type =
seems worrisome, yes. =C2=A0For example, the following trait is prone to OD=
R violations when used across translation units</div><div><br></div><div><d=
iv><font face=3D"courier new, monospace">template &lt;typename IncompleteTy=
pe, typename =3D std::enable_if_t&lt;true&gt;&gt;</font></div><div><font fa=
ce=3D"courier new, monospace">struct DetermineComplete {</font></div><div><=
font face=3D"courier new, monospace">=C2=A0 =C2=A0 static constexpr const b=
ool value =3D false;</font></div><div><font face=3D"courier new, monospace"=
>};</font></div><div><font face=3D"courier new, monospace"><br></font></div=
><div><font face=3D"courier new, monospace">template &lt;typename Incomplet=
eType&gt;</font></div><div><font face=3D"courier new, monospace">struct Det=
ermineComplete&lt;</font></div><div><font face=3D"courier new, monospace">=
=C2=A0 =C2=A0 =C2=A0 =C2=A0 IncompleteType,</font></div><div><font face=3D"=
courier new, monospace">=C2=A0 =C2=A0 =C2=A0 =C2=A0 std::enable_if_t&lt;siz=
eof(IncompleteType) =3D=3D sizeof(IncompleteType)&gt;&gt; {</font></div><di=
v><font face=3D"courier new, monospace">=C2=A0 =C2=A0 static constexpr cons=
t bool value =3D true;</font></div><div><font face=3D"courier new, monospac=
e">};</font></div></div><div><br></div><div>But when you inject the above t=
rait in an anonymous namespace, that problem seems to be mitigated? =C2=A0P=
erhaps then, the solution should be to inject the trait in an anonymous nam=
espace in the <font face=3D"courier new, monospace">&lt;type_traits&gt;</fo=
nt> header? =C2=A0This way, it will be harder to violate ODR across transla=
tion units. =C2=A0And if this is used only with structured-binding-lambdas =
then it can either cause an instantiation or not, =C2=A0I cannot picture it=
 causing two conflicting instantiations across translation units. =C2=A0May=
be it should be kept private to the implementation?</div></div><div><br></d=
iv><blockquote class=3D"gmail_quote" style=3D"margin: 0;margin-left: 0.8ex;=
border-left: 1px #ccc solid;padding-left: 1ex;"><div dir=3D"ltr"><div>Shoul=
d the trait and overload resolution do the same check, or should overload r=
esolution do a different check? For example, while overload resolution gene=
rally ignores access controls and deleted definitions, traits generally do =
not.=C2=A0</div></div></blockquote><div><br></div><div>I feel like the trai=
t should do the following checks now:</div><div><ol><li>If the type is an a=
rray type of cardinality <font face=3D"courier new, monospace">x</font>, it=
 is x-decomposable</li><li>If <font face=3D"courier new, monospace">tuple_s=
ize&lt;T&gt;</font> is a complete type for <font face=3D"courier new, monos=
pace">T</font>, and <font face=3D"courier new, monospace">tuple_size&lt;T&g=
t;::value</font> is equal to <font face=3D"courier new, monospace">x</font>=
, then the type <font face=3D"courier new, monospace">T</font> is x-decompo=
sable</li><li>If the type is decomposable into <font face=3D"courier new, m=
onospace">x</font> bindings via binding to it&#39;s <font face=3D"courier n=
ew, monospace">x</font> public data members, it is x-decomposable (referenc=
ing the same conditions as those for regular structured binding decompositi=
ons)=C2=A0<br></li></ol><div>This keeps the definition simple and the seman=
tics consistent. =C2=A0</div></div><div><br></div><blockquote class=3D"gmai=
l_quote" style=3D"margin: 0;margin-left: 0.8ex;border-left: 1px #ccc solid;=
padding-left: 1ex;"><div dir=3D"ltr"><div>The standard uses ref-qualifier f=
or the &amp;/&amp;&amp;. I hated that, which is why cppreference doesn&#39;=
t use that name, but if you are writing a paper to change the standard then=
 you should use the name in the standard.</div></div></blockquote><div><br>=
</div><div>Thanks! =C2=A0I&#39;ll make that change in the next version of t=
he paper along with the change related to the decomposable trait and concep=
t.</div></div>

<p></p>

-- <br />
You received this message because you are subscribed to the Google Groups &=
quot;ISO C++ Standard - Future Proposals&quot; group.<br />
To unsubscribe from this group and stop receiving emails from it, send an e=
mail to <a href=3D"mailto:std-proposals+unsubscribe@isocpp.org">std-proposa=
ls+unsubscribe@isocpp.org</a>.<br />
To post to this group, send email to <a href=3D"mailto:std-proposals@isocpp=
..org">std-proposals@isocpp.org</a>.<br />
To view this discussion on the web visit <a href=3D"https://groups.google.c=
om/a/isocpp.org/d/msgid/std-proposals/029d244a-cc53-40de-9c2f-59b1bc776c1b%=
40isocpp.org?utm_medium=3Demail&utm_source=3Dfooter">https://groups.google.=
com/a/isocpp.org/d/msgid/std-proposals/029d244a-cc53-40de-9c2f-59b1bc776c1b=
%40isocpp.org</a>.<br />

------=_Part_6197_1652353992.1503901738032--

------=_Part_6196_1851396653.1503901738032--

.


Author: "T. C." <rs2740@gmail.com>
Date: Mon, 28 Aug 2017 01:38:04 -0700 (PDT)
Raw View
------=_Part_6283_1253384204.1503909484358
Content-Type: multipart/alternative;
 boundary="----=_Part_6284_2019659389.1503909484359"

------=_Part_6284_2019659389.1503909484359
Content-Type: text/plain; charset="UTF-8"

You don't have to have multiple translation units to run into ODR problems.
Consider (the idea was first pointed out to me by Casey Carter a while
ago):

struct X { int a; };

template<> struct std::tuple_size<X>;
template<size_t I> struct std::tuple_element<I, X> { using type = int; };
template<size_t I> int get(X) { return 1; }


auto [a] = X(); // is_decomposable<1, X>::value == true ;
is_decomposable<3, X>::value == false ?


template<> struct std::tuple_size<X> : std::integral_constant<size_t, 3> {};
auto [b, c, d] = X();

// auto [e] = X(); // error now
// is_decomposable<1, X>::value == ?


Also, to illustrate my question about extent of the check, what should the
following code do? (This is basically GB 20's motivating example.)
struct Y {};
template<> struct std::tuple_size<Y> { const int value = 2; /* note missing
"static" */ };
// tuple_element/get omitted

static_assert(is_decomposable<2, Y>::value);

1) fire the static assert
2) somehow not fire the static assert
3) cause a hard error
4) something else

--
You received this message because you are subscribed to the Google Groups "ISO C++ Standard - Future Proposals" group.
To unsubscribe from this group and stop receiving emails from it, send an email to std-proposals+unsubscribe@isocpp.org.
To post to this group, send email to std-proposals@isocpp.org.
To view this discussion on the web visit https://groups.google.com/a/isocpp.org/d/msgid/std-proposals/481b4d44-74e0-4cd3-8141-62d35dea8350%40isocpp.org.

------=_Part_6284_2019659389.1503909484359
Content-Type: text/html; charset="UTF-8"
Content-Transfer-Encoding: quoted-printable

<div dir=3D"ltr"><div>You don&#39;t have to have multiple translation units=
 to run into ODR problems. Consider (the idea was first pointed out to me b=
y Casey Carter a while ago):=C2=A0<br></div><div><br></div><div class=3D"pr=
ettyprint" style=3D"background-color: rgb(250, 250, 250); border-color: rgb=
(187, 187, 187); border-style: solid; border-width: 1px; word-wrap: break-w=
ord;"><code class=3D"prettyprint"><div class=3D"subprettyprint"><span style=
=3D"color: #008;" class=3D"styled-by-prettify">struct</span><span style=3D"=
color: #000;" class=3D"styled-by-prettify"> X </span><span style=3D"color: =
#660;" class=3D"styled-by-prettify">{</span><span style=3D"color: #000;" cl=
ass=3D"styled-by-prettify"> </span><span style=3D"color: #008;" class=3D"st=
yled-by-prettify">int</span><span style=3D"color: #000;" class=3D"styled-by=
-prettify"> a</span><span style=3D"color: #660;" class=3D"styled-by-prettif=
y">;</span><span style=3D"color: #000;" class=3D"styled-by-prettify"> </spa=
n><span style=3D"color: #660;" class=3D"styled-by-prettify">};</span><span =
style=3D"color: #000;" class=3D"styled-by-prettify"><br><br></span><span st=
yle=3D"color: #008;" class=3D"styled-by-prettify">template</span><span styl=
e=3D"color: #660;" class=3D"styled-by-prettify">&lt;&gt;</span><span style=
=3D"color: #000;" class=3D"styled-by-prettify"> </span><span style=3D"color=
: #008;" class=3D"styled-by-prettify">struct</span><span style=3D"color: #0=
00;" class=3D"styled-by-prettify"> std</span><span style=3D"color: #660;" c=
lass=3D"styled-by-prettify">::</span><span style=3D"color: #000;" class=3D"=
styled-by-prettify">tuple_size</span><span style=3D"color: #660;" class=3D"=
styled-by-prettify">&lt;</span><span style=3D"color: #000;" class=3D"styled=
-by-prettify">X</span><span style=3D"color: #660;" class=3D"styled-by-prett=
ify">&gt;;</span><span style=3D"color: #000;" class=3D"styled-by-prettify">=
<br></span><span style=3D"color: #008;" class=3D"styled-by-prettify">templa=
te</span><span style=3D"color: #660;" class=3D"styled-by-prettify">&lt;</sp=
an><span style=3D"color: #000;" class=3D"styled-by-prettify">size_t I</span=
><span style=3D"color: #660;" class=3D"styled-by-prettify">&gt;</span><span=
 style=3D"color: #000;" class=3D"styled-by-prettify"> </span><span style=3D=
"color: #008;" class=3D"styled-by-prettify">struct</span><span style=3D"col=
or: #000;" class=3D"styled-by-prettify"> std</span><span style=3D"color: #6=
60;" class=3D"styled-by-prettify">::</span><span style=3D"color: #000;" cla=
ss=3D"styled-by-prettify">tuple_element</span><span style=3D"color: #660;" =
class=3D"styled-by-prettify">&lt;</span><span style=3D"color: #000;" class=
=3D"styled-by-prettify">I</span><span style=3D"color: #660;" class=3D"style=
d-by-prettify">,</span><span style=3D"color: #000;" class=3D"styled-by-pret=
tify"> X</span><span style=3D"color: #660;" class=3D"styled-by-prettify">&g=
t;</span><span style=3D"color: #000;" class=3D"styled-by-prettify"> </span>=
<span style=3D"color: #660;" class=3D"styled-by-prettify">{</span><span sty=
le=3D"color: #000;" class=3D"styled-by-prettify"> </span><span style=3D"col=
or: #008;" class=3D"styled-by-prettify">using</span><span style=3D"color: #=
000;" class=3D"styled-by-prettify"> type </span><span style=3D"color: #660;=
" class=3D"styled-by-prettify">=3D</span><span style=3D"color: #000;" class=
=3D"styled-by-prettify"> </span><span style=3D"color: #008;" class=3D"style=
d-by-prettify">int</span><span style=3D"color: #660;" class=3D"styled-by-pr=
ettify">;</span><span style=3D"color: #000;" class=3D"styled-by-prettify"> =
</span><span style=3D"color: #660;" class=3D"styled-by-prettify">};</span><=
span style=3D"color: #000;" class=3D"styled-by-prettify"><br></span><span s=
tyle=3D"color: #008;" class=3D"styled-by-prettify">template</span><span sty=
le=3D"color: #660;" class=3D"styled-by-prettify">&lt;</span><span style=3D"=
color: #000;" class=3D"styled-by-prettify">size_t I</span><span style=3D"co=
lor: #660;" class=3D"styled-by-prettify">&gt;</span><span style=3D"color: #=
000;" class=3D"styled-by-prettify"> </span><span style=3D"color: #008;" cla=
ss=3D"styled-by-prettify">int</span><span style=3D"color: #000;" class=3D"s=
tyled-by-prettify"> </span><span style=3D"color: #008;" class=3D"styled-by-=
prettify">get</span><span style=3D"color: #660;" class=3D"styled-by-prettif=
y">(</span><span style=3D"color: #000;" class=3D"styled-by-prettify">X</spa=
n><span style=3D"color: #660;" class=3D"styled-by-prettify">)</span><span s=
tyle=3D"color: #000;" class=3D"styled-by-prettify"> </span><span style=3D"c=
olor: #660;" class=3D"styled-by-prettify">{</span><span style=3D"color: #00=
0;" class=3D"styled-by-prettify"> </span><span style=3D"color: #008;" class=
=3D"styled-by-prettify">return</span><span style=3D"color: #000;" class=3D"=
styled-by-prettify"> </span><span style=3D"color: #066;" class=3D"styled-by=
-prettify">1</span><span style=3D"color: #660;" class=3D"styled-by-prettify=
">;</span><span style=3D"color: #000;" class=3D"styled-by-prettify"> </span=
><span style=3D"color: #660;" class=3D"styled-by-prettify">}</span><span st=
yle=3D"color: #000;" class=3D"styled-by-prettify"><br><br><br></span><span =
style=3D"color: #008;" class=3D"styled-by-prettify">auto</span><span style=
=3D"color: #000;" class=3D"styled-by-prettify"> </span><span style=3D"color=
: #660;" class=3D"styled-by-prettify">[</span><span style=3D"color: #000;" =
class=3D"styled-by-prettify">a</span><span style=3D"color: #660;" class=3D"=
styled-by-prettify">]</span><span style=3D"color: #000;" class=3D"styled-by=
-prettify"> </span><span style=3D"color: #660;" class=3D"styled-by-prettify=
">=3D</span><span style=3D"color: #000;" class=3D"styled-by-prettify"> X</s=
pan><span style=3D"color: #660;" class=3D"styled-by-prettify">();</span><sp=
an style=3D"color: #000;" class=3D"styled-by-prettify"> </span><span style=
=3D"color: #800;" class=3D"styled-by-prettify">// is_decomposable&lt;1, X&g=
t;::value =3D=3D true ; is_decomposable&lt;3, X&gt;::value =3D=3D false ?</=
span><span style=3D"color: #000;" class=3D"styled-by-prettify"><br><br><br>=
</span><span style=3D"color: #008;" class=3D"styled-by-prettify">template</=
span><span style=3D"color: #660;" class=3D"styled-by-prettify">&lt;&gt;</sp=
an><span style=3D"color: #000;" class=3D"styled-by-prettify"> </span><span =
style=3D"color: #008;" class=3D"styled-by-prettify">struct</span><span styl=
e=3D"color: #000;" class=3D"styled-by-prettify"> std</span><span style=3D"c=
olor: #660;" class=3D"styled-by-prettify">::</span><span style=3D"color: #0=
00;" class=3D"styled-by-prettify">tuple_size</span><span style=3D"color: #6=
60;" class=3D"styled-by-prettify">&lt;</span><span style=3D"color: #000;" c=
lass=3D"styled-by-prettify">X</span><span style=3D"color: #660;" class=3D"s=
tyled-by-prettify">&gt;</span><span style=3D"color: #000;" class=3D"styled-=
by-prettify"> </span><span style=3D"color: #660;" class=3D"styled-by-pretti=
fy">:</span><span style=3D"color: #000;" class=3D"styled-by-prettify"> std<=
/span><span style=3D"color: #660;" class=3D"styled-by-prettify">::</span><s=
pan style=3D"color: #000;" class=3D"styled-by-prettify">integral_constant</=
span><span style=3D"color: #660;" class=3D"styled-by-prettify">&lt;</span><=
span style=3D"color: #000;" class=3D"styled-by-prettify">size_t</span><span=
 style=3D"color: #660;" class=3D"styled-by-prettify">,</span><span style=3D=
"color: #000;" class=3D"styled-by-prettify"> </span><span style=3D"color: #=
066;" class=3D"styled-by-prettify">3</span><span style=3D"color: #660;" cla=
ss=3D"styled-by-prettify">&gt;</span><span style=3D"color: #000;" class=3D"=
styled-by-prettify"> </span><span style=3D"color: #660;" class=3D"styled-by=
-prettify">{};</span><span style=3D"color: #000;" class=3D"styled-by-pretti=
fy"><br></span><span style=3D"color: #008;" class=3D"styled-by-prettify">au=
to</span><span style=3D"color: #000;" class=3D"styled-by-prettify"> </span>=
<span style=3D"color: #660;" class=3D"styled-by-prettify">[</span><span sty=
le=3D"color: #000;" class=3D"styled-by-prettify">b</span><span style=3D"col=
or: #660;" class=3D"styled-by-prettify">,</span><span style=3D"color: #000;=
" class=3D"styled-by-prettify"> c</span><span style=3D"color: #660;" class=
=3D"styled-by-prettify">,</span><span style=3D"color: #000;" class=3D"style=
d-by-prettify"> d</span><span style=3D"color: #660;" class=3D"styled-by-pre=
ttify">]</span><span style=3D"color: #000;" class=3D"styled-by-prettify"> <=
/span><span style=3D"color: #660;" class=3D"styled-by-prettify">=3D</span><=
span style=3D"color: #000;" class=3D"styled-by-prettify"> X</span><span sty=
le=3D"color: #660;" class=3D"styled-by-prettify">();</span><span style=3D"c=
olor: #000;" class=3D"styled-by-prettify"><br><br></span><span style=3D"col=
or: #800;" class=3D"styled-by-prettify">// auto [e] =3D X(); // error now</=
span><span style=3D"color: #000;" class=3D"styled-by-prettify"><br></span><=
span style=3D"color: #800;" class=3D"styled-by-prettify">// is_decomposable=
&lt;1, X&gt;::value =3D=3D ?</span><span style=3D"color: #000;" class=3D"st=
yled-by-prettify"><br><br></span></div></code></div><div><br></div><div>Als=
o, to illustrate my question about extent of the check, what should the fol=
lowing code do? (This is basically GB 20&#39;s motivating example.)</div><d=
iv><div class=3D"prettyprint" style=3D"background-color: rgb(250, 250, 250)=
; border-color: rgb(187, 187, 187); border-style: solid; border-width: 1px;=
 word-wrap: break-word;"><code class=3D"prettyprint"><div class=3D"subprett=
yprint"><font color=3D"#660066"><span style=3D"color: #008;" class=3D"style=
d-by-prettify">struct</span><span style=3D"color: #000;" class=3D"styled-by=
-prettify"> Y </span><span style=3D"color: #660;" class=3D"styled-by-pretti=
fy">{};</span><span style=3D"color: #000;" class=3D"styled-by-prettify"><br=
></span><span style=3D"color: #008;" class=3D"styled-by-prettify">template<=
/span><span style=3D"color: #660;" class=3D"styled-by-prettify">&lt;&gt;</s=
pan><span style=3D"color: #000;" class=3D"styled-by-prettify"> </span><span=
 style=3D"color: #008;" class=3D"styled-by-prettify">struct</span><span sty=
le=3D"color: #000;" class=3D"styled-by-prettify"> std</span><span style=3D"=
color: #660;" class=3D"styled-by-prettify">::</span><span style=3D"color: #=
000;" class=3D"styled-by-prettify">tuple_size</span><span style=3D"color: #=
660;" class=3D"styled-by-prettify">&lt;</span><span style=3D"color: #000;" =
class=3D"styled-by-prettify">Y</span><span style=3D"color: #660;" class=3D"=
styled-by-prettify">&gt;</span><span style=3D"color: #000;" class=3D"styled=
-by-prettify"> </span><span style=3D"color: #660;" class=3D"styled-by-prett=
ify">{</span><span style=3D"color: #000;" class=3D"styled-by-prettify"> </s=
pan><span style=3D"color: #008;" class=3D"styled-by-prettify">const</span><=
span style=3D"color: #000;" class=3D"styled-by-prettify"> </span><span styl=
e=3D"color: #008;" class=3D"styled-by-prettify">int</span><span style=3D"co=
lor: #000;" class=3D"styled-by-prettify"> value </span><span style=3D"color=
: #660;" class=3D"styled-by-prettify">=3D</span><span style=3D"color: #000;=
" class=3D"styled-by-prettify"> </span><span style=3D"color: #066;" class=
=3D"styled-by-prettify">2</span><span style=3D"color: #660;" class=3D"style=
d-by-prettify">;</span><span style=3D"color: #000;" class=3D"styled-by-pret=
tify"> </span><span style=3D"color: #800;" class=3D"styled-by-prettify">/* =
note missing &quot;static&quot; */</span><span style=3D"color: #000;" class=
=3D"styled-by-prettify"> </span><span style=3D"color: #660;" class=3D"style=
d-by-prettify">};</span><span style=3D"color: #000;" class=3D"styled-by-pre=
ttify"><br></span><span style=3D"color: #800;" class=3D"styled-by-prettify"=
>// tuple_element/get omitted</span><span style=3D"color: #000;" class=3D"s=
tyled-by-prettify"><br><br></span><span style=3D"color: #008;" class=3D"sty=
led-by-prettify">static_assert</span><span style=3D"color: #660;" class=3D"=
styled-by-prettify">(</span><span style=3D"color: #000;" class=3D"styled-by=
-prettify">is_decomposable</span><span style=3D"color: #660;" class=3D"styl=
ed-by-prettify">&lt;</span><span style=3D"color: #066;" class=3D"styled-by-=
prettify">2</span><span style=3D"color: #660;" class=3D"styled-by-prettify"=
>,</span><span style=3D"color: #000;" class=3D"styled-by-prettify"> Y</span=
><span style=3D"color: #660;" class=3D"styled-by-prettify">&gt;::</span><sp=
an style=3D"color: #000;" class=3D"styled-by-prettify">value</span><span st=
yle=3D"color: #660;" class=3D"styled-by-prettify">);</span></font></div></c=
ode></div><br></div><div>1) fire the static assert</div><div>2) somehow not=
 fire the static assert</div><div>3) cause a hard error</div><div>4) someth=
ing else</div></div>

<p></p>

-- <br />
You received this message because you are subscribed to the Google Groups &=
quot;ISO C++ Standard - Future Proposals&quot; group.<br />
To unsubscribe from this group and stop receiving emails from it, send an e=
mail to <a href=3D"mailto:std-proposals+unsubscribe@isocpp.org">std-proposa=
ls+unsubscribe@isocpp.org</a>.<br />
To post to this group, send email to <a href=3D"mailto:std-proposals@isocpp=
..org">std-proposals@isocpp.org</a>.<br />
To view this discussion on the web visit <a href=3D"https://groups.google.c=
om/a/isocpp.org/d/msgid/std-proposals/481b4d44-74e0-4cd3-8141-62d35dea8350%=
40isocpp.org?utm_medium=3Demail&utm_source=3Dfooter">https://groups.google.=
com/a/isocpp.org/d/msgid/std-proposals/481b4d44-74e0-4cd3-8141-62d35dea8350=
%40isocpp.org</a>.<br />

------=_Part_6284_2019659389.1503909484359--

------=_Part_6283_1253384204.1503909484358--

.


Author: Curious <rmn100@gmail.com>
Date: Mon, 28 Aug 2017 09:44:47 -0700 (PDT)
Raw View
------=_Part_6864_489392449.1503938687379
Content-Type: multipart/alternative;
 boundary="----=_Part_6865_1116938480.1503938687380"

------=_Part_6865_1116938480.1503938687380
Content-Type: text/plain; charset="UTF-8"

You are right.  This makes me wonder.  Are structured bindings not prone to
the same problems?  The structured bindings decomposition checks to see if
tuple_size<> is a complete type first, and then go on to check if the class
can be decomposed via it's public members.  For example

class Something {
public:
    int a;
};

namespace std {
template <>
class tuple_size<Something>;
} // namespace std

template <typename SomethingType>
void foo(SomethingType something) {
    auto [one] = something;
    static_cast<void>(one);
}

void bar(Something something) {
    foo(something);
}

/**
 * Define the tuple shenanigans
 */
namespace std {
template <>
class tuple_size<Something> : std::integral_constant<int, 1> {};
template <std::size_t Index>
class tuple_element<Index, Something> {
    using type = int;
}
template <std::size_t Index>
int get(Something something) {
    std::cout << "get(Something)" << std::endl;
    return something.a;
}
} // namespace std

void baz(Something something) {
    // now expect logging
    foo(something);
}

Although I suspect the above isn't an ODR problem because the bindings
aren't involved in the template instantiation process.  Although it might
be surprising to the user.

I wonder why a simpler approach wasn't taken, why check for tuple_size<> to
be a complete type rather than checking for the existence of a static
constexpr value or a std::integral_constant<> typedef within the class?
 This can now be a possible change, instead of allowing tuple_size<> to be
specialized everywhere.  Make classes that want to pretend to be a tuple
have a member typedef or a static constexpr and make tuple_size<> use that
typedef in the general case, and don't leave the type undefined (I suspect
this will break a lot of code, if people are checking to see if
tuple_size<> is a complete type).  For example

class TupleLike {
public:
    using tuple_size_type = std::integral_constant<int, 2>;
private:
    std::tuple<int, int> a;
};

This is much simpler and is not prone to ODR issues.  And now structured
bindings can check for the existence of and inspect the tuple_size_type
alias within the class.

And then in the general case tuple_size<> can be defined like

namespace std {
template <typename T>
class tuple_size {
 static constexpr const auto value = T::tuple_size_type::value;
};

} // namespace std

The second simpler solution to the is_decomposable problem is to not use
the trait at all, and just let the lambda translate to an unconstrained
template function in an anonymous class.

Also, to illustrate my question about extent of the check, what should the
> following code do? (This is basically GB 20's motivating example.)
>

Shouldn't this cause a hard error?  std::tuple_size is defined, and when
the code tries to use it, it finds out that the specialization is just
incorrectly defined.

--
You received this message because you are subscribed to the Google Groups "ISO C++ Standard - Future Proposals" group.
To unsubscribe from this group and stop receiving emails from it, send an email to std-proposals+unsubscribe@isocpp.org.
To post to this group, send email to std-proposals@isocpp.org.
To view this discussion on the web visit https://groups.google.com/a/isocpp.org/d/msgid/std-proposals/cfbbbe0f-cace-46ce-977a-ac57b9c3003e%40isocpp.org.

------=_Part_6865_1116938480.1503938687380
Content-Type: text/html; charset="UTF-8"
Content-Transfer-Encoding: quoted-printable

<div dir=3D"ltr">You are right. =C2=A0This makes me wonder. =C2=A0Are struc=
tured bindings not prone to the same problems? =C2=A0The structured binding=
s decomposition checks to see if <font face=3D"courier new, monospace">tupl=
e_size&lt;&gt;</font> is a complete type first, and then go on to check if =
the class can be decomposed via it&#39;s public members. =C2=A0For example<=
div><br></div><div><div class=3D"prettyprint" style=3D"background-color: rg=
b(250, 250, 250); border: 1px solid rgb(187, 187, 187); word-wrap: break-wo=
rd;"><code class=3D"prettyprint"><div class=3D"subprettyprint"><span style=
=3D"color: #008;" class=3D"styled-by-prettify">class</span><span style=3D"c=
olor: #000;" class=3D"styled-by-prettify"> </span><span style=3D"color: #60=
6;" class=3D"styled-by-prettify">Something</span><span style=3D"color: #000=
;" class=3D"styled-by-prettify"> </span><span style=3D"color: #660;" class=
=3D"styled-by-prettify">{</span><span style=3D"color: #000;" class=3D"style=
d-by-prettify"><br></span><span style=3D"color: #008;" class=3D"styled-by-p=
rettify">public</span><span style=3D"color: #660;" class=3D"styled-by-prett=
ify">:</span><span style=3D"color: #000;" class=3D"styled-by-prettify"><br>=
=C2=A0 =C2=A0 </span><span style=3D"color: #008;" class=3D"styled-by-pretti=
fy">int</span><span style=3D"color: #000;" class=3D"styled-by-prettify"> a<=
/span><span style=3D"color: #660;" class=3D"styled-by-prettify">;</span><sp=
an style=3D"color: #000;" class=3D"styled-by-prettify"><br></span><span sty=
le=3D"color: #660;" class=3D"styled-by-prettify">};</span><span style=3D"co=
lor: #000;" class=3D"styled-by-prettify"><br><br></span><span style=3D"colo=
r: #008;" class=3D"styled-by-prettify">namespace</span><span style=3D"color=
: #000;" class=3D"styled-by-prettify"> std </span><span style=3D"color: #66=
0;" class=3D"styled-by-prettify">{</span><span style=3D"color: #000;" class=
=3D"styled-by-prettify"><br></span><span style=3D"color: #008;" class=3D"st=
yled-by-prettify">template</span><span style=3D"color: #000;" class=3D"styl=
ed-by-prettify"> </span><span style=3D"color: #660;" class=3D"styled-by-pre=
ttify">&lt;&gt;</span><span style=3D"color: #000;" class=3D"styled-by-prett=
ify"><br></span><span style=3D"color: #008;" class=3D"styled-by-prettify">c=
lass</span><span style=3D"color: #000;" class=3D"styled-by-prettify"> tuple=
_size</span><span style=3D"color: #660;" class=3D"styled-by-prettify">&lt;<=
/span><span style=3D"color: #606;" class=3D"styled-by-prettify">Something</=
span><span style=3D"color: #660;" class=3D"styled-by-prettify">&gt;;</span>=
<span style=3D"color: #000;" class=3D"styled-by-prettify"><br></span><span =
style=3D"color: #660;" class=3D"styled-by-prettify">}</span><span style=3D"=
color: #000;" class=3D"styled-by-prettify"> </span><span style=3D"color: #8=
00;" class=3D"styled-by-prettify">// namespace std</span><span style=3D"col=
or: #000;" class=3D"styled-by-prettify"><br>=C2=A0 =C2=A0 <br></span><span =
style=3D"color: #008;" class=3D"styled-by-prettify">template</span><span st=
yle=3D"color: #000;" class=3D"styled-by-prettify"> </span><span style=3D"co=
lor: #660;" class=3D"styled-by-prettify">&lt;</span><span style=3D"color: #=
008;" class=3D"styled-by-prettify">typename</span><span style=3D"color: #00=
0;" class=3D"styled-by-prettify"> </span><span style=3D"color: #606;" class=
=3D"styled-by-prettify">SomethingType</span><span style=3D"color: #660;" cl=
ass=3D"styled-by-prettify">&gt;</span><span style=3D"color: #000;" class=3D=
"styled-by-prettify"><br></span><span style=3D"color: #008;" class=3D"style=
d-by-prettify">void</span><span style=3D"color: #000;" class=3D"styled-by-p=
rettify"> foo</span><span style=3D"color: #660;" class=3D"styled-by-prettif=
y">(</span><span style=3D"color: #606;" class=3D"styled-by-prettify">Someth=
ingType</span><span style=3D"color: #000;" class=3D"styled-by-prettify"> so=
mething</span><span style=3D"color: #660;" class=3D"styled-by-prettify">)</=
span><span style=3D"color: #000;" class=3D"styled-by-prettify"> </span><spa=
n style=3D"color: #660;" class=3D"styled-by-prettify">{</span><span style=
=3D"color: #000;" class=3D"styled-by-prettify"><br>=C2=A0 =C2=A0 </span><sp=
an style=3D"color: #008;" class=3D"styled-by-prettify">auto</span><span sty=
le=3D"color: #000;" class=3D"styled-by-prettify"> </span><span style=3D"col=
or: #660;" class=3D"styled-by-prettify">[</span><span style=3D"color: #000;=
" class=3D"styled-by-prettify">one</span><span style=3D"color: #660;" class=
=3D"styled-by-prettify">]</span><span style=3D"color: #000;" class=3D"style=
d-by-prettify"> </span><span style=3D"color: #660;" class=3D"styled-by-pret=
tify">=3D</span><span style=3D"color: #000;" class=3D"styled-by-prettify"> =
something</span><span style=3D"color: #660;" class=3D"styled-by-prettify">;=
</span><span style=3D"color: #000;" class=3D"styled-by-prettify"><br>=C2=A0=
 =C2=A0 </span><span style=3D"color: #008;" class=3D"styled-by-prettify">st=
atic_cast</span><span style=3D"color: #080;" class=3D"styled-by-prettify">&=
lt;void&gt;</span><span style=3D"color: #660;" class=3D"styled-by-prettify"=
>(</span><span style=3D"color: #000;" class=3D"styled-by-prettify">one</spa=
n><span style=3D"color: #660;" class=3D"styled-by-prettify">);</span><span =
style=3D"color: #000;" class=3D"styled-by-prettify"><br></span><span style=
=3D"color: #660;" class=3D"styled-by-prettify">}</span><span style=3D"color=
: #000;" class=3D"styled-by-prettify"><br><br></span><span style=3D"color: =
#008;" class=3D"styled-by-prettify">void</span><span style=3D"color: #000;"=
 class=3D"styled-by-prettify"> bar</span><span style=3D"color: #660;" class=
=3D"styled-by-prettify">(</span><span style=3D"color: #606;" class=3D"style=
d-by-prettify">Something</span><span style=3D"color: #000;" class=3D"styled=
-by-prettify"> something</span><span style=3D"color: #660;" class=3D"styled=
-by-prettify">)</span><span style=3D"color: #000;" class=3D"styled-by-prett=
ify"> </span><span style=3D"color: #660;" class=3D"styled-by-prettify">{</s=
pan><span style=3D"color: #000;" class=3D"styled-by-prettify"><br>=C2=A0 =
=C2=A0 foo</span><span style=3D"color: #660;" class=3D"styled-by-prettify">=
(</span><span style=3D"color: #000;" class=3D"styled-by-prettify">something=
</span><span style=3D"color: #660;" class=3D"styled-by-prettify">);</span><=
span style=3D"color: #000;" class=3D"styled-by-prettify"><br></span><span s=
tyle=3D"color: #660;" class=3D"styled-by-prettify">}</span><span style=3D"c=
olor: #000;" class=3D"styled-by-prettify"><br><br></span><span style=3D"col=
or: #800;" class=3D"styled-by-prettify">/**<br>=C2=A0* Define the tuple </s=
pan><span style=3D"color: #800;" class=3D"styled-by-prettify">shenanigans<b=
r>=C2=A0*/</span><span style=3D"color: #000;" class=3D"styled-by-prettify">=
<br></span><span style=3D"color: #008;" class=3D"styled-by-prettify">namesp=
ace</span><span style=3D"color: #000;" class=3D"styled-by-prettify"> std </=
span><span style=3D"color: #660;" class=3D"styled-by-prettify">{</span><spa=
n style=3D"color: #000;" class=3D"styled-by-prettify"><br></span><span styl=
e=3D"color: #008;" class=3D"styled-by-prettify">template</span><span style=
=3D"color: #000;" class=3D"styled-by-prettify"> </span><span style=3D"color=
: #660;" class=3D"styled-by-prettify">&lt;&gt;</span><span style=3D"color: =
#000;" class=3D"styled-by-prettify"><br></span><span style=3D"color: #008;"=
 class=3D"styled-by-prettify">class</span><span style=3D"color: #000;" clas=
s=3D"styled-by-prettify"> tuple_size</span><span style=3D"color: #660;" cla=
ss=3D"styled-by-prettify">&lt;</span><span style=3D"color: #606;" class=3D"=
styled-by-prettify">Something</span><span style=3D"color: #660;" class=3D"s=
tyled-by-prettify">&gt;</span><span style=3D"color: #000;" class=3D"styled-=
by-prettify"> </span><span style=3D"color: #660;" class=3D"styled-by-pretti=
fy">:</span><span style=3D"color: #000;" class=3D"styled-by-prettify"> std<=
/span><span style=3D"color: #660;" class=3D"styled-by-prettify">::</span><s=
pan style=3D"color: #000;" class=3D"styled-by-prettify">integral_constant</=
span><span style=3D"color: #660;" class=3D"styled-by-prettify">&lt;</span><=
span style=3D"color: #008;" class=3D"styled-by-prettify">int</span><span st=
yle=3D"color: #660;" class=3D"styled-by-prettify">,</span><span style=3D"co=
lor: #000;" class=3D"styled-by-prettify"> </span><span style=3D"color: #066=
;" class=3D"styled-by-prettify">1</span><span style=3D"color: #660;" class=
=3D"styled-by-prettify">&gt;</span><span style=3D"color: #000;" class=3D"st=
yled-by-prettify"> </span><span style=3D"color: #660;" class=3D"styled-by-p=
rettify">{};</span><span style=3D"color: #000;" class=3D"styled-by-prettify=
"><br></span><span style=3D"color: #008;" class=3D"styled-by-prettify">temp=
late</span><span style=3D"color: #000;" class=3D"styled-by-prettify"> </spa=
n><span style=3D"color: #660;" class=3D"styled-by-prettify">&lt;</span><spa=
n style=3D"color: #000;" class=3D"styled-by-prettify">std</span><span style=
=3D"color: #660;" class=3D"styled-by-prettify">::</span><span style=3D"colo=
r: #000;" class=3D"styled-by-prettify">size_t </span><span style=3D"color: =
#606;" class=3D"styled-by-prettify">Index</span><span style=3D"color: #660;=
" class=3D"styled-by-prettify">&gt;</span><span style=3D"color: #000;" clas=
s=3D"styled-by-prettify"><br></span><span style=3D"color: #008;" class=3D"s=
tyled-by-prettify">class</span><span style=3D"color: #000;" class=3D"styled=
-by-prettify"> tuple_element</span><span style=3D"color: #660;" class=3D"st=
yled-by-prettify">&lt;</span><span style=3D"color: #606;" class=3D"styled-b=
y-prettify">Index</span><span style=3D"color: #660;" class=3D"styled-by-pre=
ttify">,</span><span style=3D"color: #000;" class=3D"styled-by-prettify"> <=
/span><span style=3D"color: #606;" class=3D"styled-by-prettify">Something</=
span><span style=3D"color: #660;" class=3D"styled-by-prettify">&gt;</span><=
span style=3D"color: #000;" class=3D"styled-by-prettify"> </span><span styl=
e=3D"color: #660;" class=3D"styled-by-prettify">{</span><span style=3D"colo=
r: #000;" class=3D"styled-by-prettify"><br>=C2=A0 =C2=A0 </span><span style=
=3D"color: #008;" class=3D"styled-by-prettify">using</span><span style=3D"c=
olor: #000;" class=3D"styled-by-prettify"> type </span><span style=3D"color=
: #660;" class=3D"styled-by-prettify">=3D</span><span style=3D"color: #000;=
" class=3D"styled-by-prettify"> </span><span style=3D"color: #008;" class=
=3D"styled-by-prettify">int</span><span style=3D"color: #660;" class=3D"sty=
led-by-prettify">;</span><span style=3D"color: #000;" class=3D"styled-by-pr=
ettify"><br></span><span style=3D"color: #660;" class=3D"styled-by-prettify=
">}</span><span style=3D"color: #000;" class=3D"styled-by-prettify"><br></s=
pan><span style=3D"color: #008;" class=3D"styled-by-prettify">template</spa=
n><span style=3D"color: #000;" class=3D"styled-by-prettify"> </span><span s=
tyle=3D"color: #660;" class=3D"styled-by-prettify">&lt;</span><span style=
=3D"color: #000;" class=3D"styled-by-prettify">std</span><span style=3D"col=
or: #660;" class=3D"styled-by-prettify">::</span><span style=3D"color: #000=
;" class=3D"styled-by-prettify">size_t </span><span style=3D"color: #606;" =
class=3D"styled-by-prettify">Index</span><span style=3D"color: #660;" class=
=3D"styled-by-prettify">&gt;</span><span style=3D"color: #000;" class=3D"st=
yled-by-prettify"><br></span><span style=3D"color: #008;" class=3D"styled-b=
y-prettify">int</span><span style=3D"color: #000;" class=3D"styled-by-prett=
ify"> </span><span style=3D"color: #008;" class=3D"styled-by-prettify">get<=
/span><span style=3D"color: #660;" class=3D"styled-by-prettify">(</span><sp=
an style=3D"color: #606;" class=3D"styled-by-prettify">Something</span><spa=
n style=3D"color: #000;" class=3D"styled-by-prettify"> something</span><spa=
n style=3D"color: #660;" class=3D"styled-by-prettify">)</span><span style=
=3D"color: #000;" class=3D"styled-by-prettify"> </span><span style=3D"color=
: #660;" class=3D"styled-by-prettify">{</span><span style=3D"color: #000;" =
class=3D"styled-by-prettify"><br>=C2=A0 =C2=A0 std</span><span style=3D"col=
or: #660;" class=3D"styled-by-prettify">::</span><span style=3D"color: #000=
;" class=3D"styled-by-prettify">cout </span><span style=3D"color: #660;" cl=
ass=3D"styled-by-prettify">&lt;&lt;</span><span style=3D"color: #000;" clas=
s=3D"styled-by-prettify"> </span><span style=3D"color: #080;" class=3D"styl=
ed-by-prettify">&quot;get(Something)&quot;</span><span style=3D"color: #000=
;" class=3D"styled-by-prettify"> </span><span style=3D"color: #660;" class=
=3D"styled-by-prettify">&lt;&lt;</span><span style=3D"color: #000;" class=
=3D"styled-by-prettify"> std</span><span style=3D"color: #660;" class=3D"st=
yled-by-prettify">::</span><span style=3D"color: #000;" class=3D"styled-by-=
prettify">endl</span><span style=3D"color: #660;" class=3D"styled-by-pretti=
fy">;</span><span style=3D"color: #000;" class=3D"styled-by-prettify"><br>=
=C2=A0 =C2=A0 </span><span style=3D"color: #008;" class=3D"styled-by-pretti=
fy">return</span><span style=3D"color: #000;" class=3D"styled-by-prettify">=
 something</span><span style=3D"color: #660;" class=3D"styled-by-prettify">=
..</span><span style=3D"color: #000;" class=3D"styled-by-prettify">a</span><=
span style=3D"color: #660;" class=3D"styled-by-prettify">;</span><span styl=
e=3D"color: #000;" class=3D"styled-by-prettify"><br></span><span style=3D"c=
olor: #660;" class=3D"styled-by-prettify">}</span><span style=3D"color: #00=
0;" class=3D"styled-by-prettify"><br></span><span style=3D"color: #660;" cl=
ass=3D"styled-by-prettify">}</span><span style=3D"color: #000;" class=3D"st=
yled-by-prettify"> </span><span style=3D"color: #800;" class=3D"styled-by-p=
rettify">// namespace std</span><span style=3D"color: #000;" class=3D"style=
d-by-prettify"><br><br></span><span style=3D"color: #008;" class=3D"styled-=
by-prettify">void</span><span style=3D"color: #000;" class=3D"styled-by-pre=
ttify"> baz</span><span style=3D"color: #660;" class=3D"styled-by-prettify"=
>(</span><span style=3D"color: #606;" class=3D"styled-by-prettify">Somethin=
g</span><span style=3D"color: #000;" class=3D"styled-by-prettify"> somethin=
g</span><span style=3D"color: #660;" class=3D"styled-by-prettify">)</span><=
span style=3D"color: #000;" class=3D"styled-by-prettify"> </span><span styl=
e=3D"color: #660;" class=3D"styled-by-prettify">{</span><span style=3D"colo=
r: #000;" class=3D"styled-by-prettify"><br>=C2=A0 =C2=A0 </span><span style=
=3D"color: #800;" class=3D"styled-by-prettify">// now expect logging</span>=
<span style=3D"color: #000;" class=3D"styled-by-prettify"><br>=C2=A0 =C2=A0=
 foo</span><span style=3D"color: #660;" class=3D"styled-by-prettify">(</spa=
n><span style=3D"color: #000;" class=3D"styled-by-prettify">something</span=
><span style=3D"color: #660;" class=3D"styled-by-prettify">);</span><span s=
tyle=3D"color: #000;" class=3D"styled-by-prettify"><br></span><span style=
=3D"color: #660;" class=3D"styled-by-prettify">}</span><span style=3D"color=
: #000;" class=3D"styled-by-prettify"><br></span></div></code></div><div><b=
r></div><div>Although I suspect the above isn&#39;t an ODR problem because =
the bindings aren&#39;t involved in the template instantiation process. =C2=
=A0Although it might be surprising to the user. =C2=A0</div><div><br></div>=
<div>I wonder why a simpler approach wasn&#39;t taken, why check for tuple_=
size&lt;&gt; to be a complete type rather than checking for the existence o=
f a static constexpr value or a std::integral_constant&lt;&gt; typedef with=
in the class? =C2=A0This can now be a possible change, instead of allowing =
tuple_size&lt;&gt; to be specialized everywhere. =C2=A0Make classes that wa=
nt to pretend to be a tuple have a member typedef or a static constexpr and=
 make tuple_size&lt;&gt; use that typedef in the general case, and don&#39;=
t leave the type undefined (I suspect this will break a lot of code, if peo=
ple are checking to see if tuple_size&lt;&gt; is a complete type). =C2=A0Fo=
r example</div><div><br></div><div class=3D"prettyprint" style=3D"backgroun=
d-color: rgb(250, 250, 250); border: 1px solid rgb(187, 187, 187); word-wra=
p: break-word;"><code class=3D"prettyprint"><div class=3D"subprettyprint"><=
span style=3D"color: #008;" class=3D"styled-by-prettify">class</span><span =
style=3D"color: #000;" class=3D"styled-by-prettify"> </span><span style=3D"=
color: #606;" class=3D"styled-by-prettify">TupleLike</span><span style=3D"c=
olor: #000;" class=3D"styled-by-prettify"> </span><span style=3D"color: #66=
0;" class=3D"styled-by-prettify">{</span><span style=3D"color: #000;" class=
=3D"styled-by-prettify"><br></span><span style=3D"color: #008;" class=3D"st=
yled-by-prettify">public</span><span style=3D"color: #660;" class=3D"styled=
-by-prettify">:</span><span style=3D"color: #000;" class=3D"styled-by-prett=
ify"> =C2=A0<br>=C2=A0 =C2=A0 </span><span style=3D"color: #008;" class=3D"=
styled-by-prettify">using</span><span style=3D"color: #000;" class=3D"style=
d-by-prettify"> tuple_size_type </span><span style=3D"color: #660;" class=
=3D"styled-by-prettify">=3D</span><span style=3D"color: #000;" class=3D"sty=
led-by-prettify"> std</span><span style=3D"color: #660;" class=3D"styled-by=
-prettify">::</span><span style=3D"color: #000;" class=3D"styled-by-prettif=
y">integral_constant</span><span style=3D"color: #660;" class=3D"styled-by-=
prettify">&lt;</span><span style=3D"color: #008;" class=3D"styled-by-pretti=
fy">int</span><span style=3D"color: #660;" class=3D"styled-by-prettify">,</=
span><span style=3D"color: #000;" class=3D"styled-by-prettify"> </span><spa=
n style=3D"color: #066;" class=3D"styled-by-prettify">2</span><span style=
=3D"color: #660;" class=3D"styled-by-prettify">&gt;;</span><span style=3D"c=
olor: #000;" class=3D"styled-by-prettify"><br></span><span style=3D"color: =
#008;" class=3D"styled-by-prettify">private</span><span style=3D"color: #66=
0;" class=3D"styled-by-prettify">:</span><span style=3D"color: #000;" class=
=3D"styled-by-prettify"><br>=C2=A0 =C2=A0 std</span><span style=3D"color: #=
660;" class=3D"styled-by-prettify">::</span><span style=3D"color: #000;" cl=
ass=3D"styled-by-prettify">tuple</span><span style=3D"color: #660;" class=
=3D"styled-by-prettify">&lt;</span><span style=3D"color: #008;" class=3D"st=
yled-by-prettify">int</span><span style=3D"color: #660;" class=3D"styled-by=
-prettify">,</span><span style=3D"color: #000;" class=3D"styled-by-prettify=
"> </span><span style=3D"color: #008;" class=3D"styled-by-prettify">int</sp=
an><span style=3D"color: #660;" class=3D"styled-by-prettify">&gt;</span><sp=
an style=3D"color: #000;" class=3D"styled-by-prettify"> a</span><span style=
=3D"color: #660;" class=3D"styled-by-prettify">;</span><span style=3D"color=
: #000;" class=3D"styled-by-prettify"><br></span><span style=3D"color: #660=
;" class=3D"styled-by-prettify">};</span></div></code></div><div><br></div>=
<div>This is much simpler and is not prone to ODR issues. =C2=A0And now str=
uctured bindings can check for the existence of and inspect the <font face=
=3D"courier new, monospace">tuple_size_type</font> alias within the class. =
=C2=A0</div><div><br></div><div>And then in the general case <font face=3D"=
courier new, monospace">tuple_size&lt;&gt;</font> can be defined like=C2=A0=
</div><div><br></div><div class=3D"prettyprint" style=3D"background-color: =
rgb(250, 250, 250); border: 1px solid rgb(187, 187, 187); word-wrap: break-=
word;"><code class=3D"prettyprint"><div class=3D"subprettyprint"><span styl=
e=3D"color: #008;" class=3D"styled-by-prettify">namespace</span><span style=
=3D"color: #000;" class=3D"styled-by-prettify"> std </span><span style=3D"c=
olor: #660;" class=3D"styled-by-prettify">{</span><span style=3D"color: #00=
0;" class=3D"styled-by-prettify"><br></span><span style=3D"color: #008;" cl=
ass=3D"styled-by-prettify">template</span><span style=3D"color: #000;" clas=
s=3D"styled-by-prettify"> </span><span style=3D"color: #660;" class=3D"styl=
ed-by-prettify">&lt;</span><span style=3D"color: #008;" class=3D"styled-by-=
prettify">typename</span><span style=3D"color: #000;" class=3D"styled-by-pr=
ettify"> T</span><span style=3D"color: #660;" class=3D"styled-by-prettify">=
&gt;</span><span style=3D"color: #000;" class=3D"styled-by-prettify"><br></=
span><span style=3D"color: #008;" class=3D"styled-by-prettify">class</span>=
<span style=3D"color: #000;" class=3D"styled-by-prettify"> tuple_size </spa=
n><span style=3D"color: #660;" class=3D"styled-by-prettify">{</span><span s=
tyle=3D"color: #000;" class=3D"styled-by-prettify"><br>=C2=A0</span><span s=
tyle=3D"color: #008;" class=3D"styled-by-prettify">static</span><span style=
=3D"color: #000;" class=3D"styled-by-prettify"> </span><span style=3D"color=
: #008;" class=3D"styled-by-prettify">constexpr</span><span style=3D"color:=
 #000;" class=3D"styled-by-prettify"> </span><span style=3D"color: #008;" c=
lass=3D"styled-by-prettify">const</span><span style=3D"color: #000;" class=
=3D"styled-by-prettify"> </span><span style=3D"color: #008;" class=3D"style=
d-by-prettify">auto</span><span style=3D"color: #000;" class=3D"styled-by-p=
rettify"> value </span><span style=3D"color: #660;" class=3D"styled-by-pret=
tify">=3D</span><span style=3D"color: #000;" class=3D"styled-by-prettify"> =
T</span><span style=3D"color: #660;" class=3D"styled-by-prettify">::</span>=
<span style=3D"color: #000;" class=3D"styled-by-prettify">tuple_size_type</=
span><span style=3D"color: #660;" class=3D"styled-by-prettify">::</span><sp=
an style=3D"color: #000;" class=3D"styled-by-prettify">value</span><span st=
yle=3D"color: #660;" class=3D"styled-by-prettify">;</span><span style=3D"co=
lor: #000;" class=3D"styled-by-prettify"><br></span><span style=3D"color: #=
660;" class=3D"styled-by-prettify">};</span><span style=3D"color: #000;" cl=
ass=3D"styled-by-prettify"><br><br></span><span style=3D"color: #660;" clas=
s=3D"styled-by-prettify">}</span><span style=3D"color: #000;" class=3D"styl=
ed-by-prettify"> </span><span style=3D"color: #800;" class=3D"styled-by-pre=
ttify">// namespace std</span><span style=3D"color: #000;" class=3D"styled-=
by-prettify"><br></span></div></code></div><div><br>The second simpler solu=
tion to the <font face=3D"courier new, monospace">is_decomposable</font> pr=
oblem is to not use the trait at all, and just let the lambda translate to =
an unconstrained template function in an anonymous class.</div><div><br></d=
iv><blockquote class=3D"gmail_quote" style=3D"margin: 0;margin-left: 0.8ex;=
border-left: 1px #ccc solid;padding-left: 1ex;"><div dir=3D"ltr"><div>Also,=
 to illustrate my question about extent of the check, what should the follo=
wing code do? (This is basically GB 20&#39;s motivating example.)</div></di=
v></blockquote><div><br></div><div>Shouldn&#39;t this cause a hard error? =
=C2=A0<font face=3D"courier new, monospace">std::tuple_size</font> is defin=
ed, and when the code tries to use it, it finds out that the specialization=
 is just incorrectly defined.</div></div></div>

<p></p>

-- <br />
You received this message because you are subscribed to the Google Groups &=
quot;ISO C++ Standard - Future Proposals&quot; group.<br />
To unsubscribe from this group and stop receiving emails from it, send an e=
mail to <a href=3D"mailto:std-proposals+unsubscribe@isocpp.org">std-proposa=
ls+unsubscribe@isocpp.org</a>.<br />
To post to this group, send email to <a href=3D"mailto:std-proposals@isocpp=
..org">std-proposals@isocpp.org</a>.<br />
To view this discussion on the web visit <a href=3D"https://groups.google.c=
om/a/isocpp.org/d/msgid/std-proposals/cfbbbe0f-cace-46ce-977a-ac57b9c3003e%=
40isocpp.org?utm_medium=3Demail&utm_source=3Dfooter">https://groups.google.=
com/a/isocpp.org/d/msgid/std-proposals/cfbbbe0f-cace-46ce-977a-ac57b9c3003e=
%40isocpp.org</a>.<br />

------=_Part_6865_1116938480.1503938687380--

------=_Part_6864_489392449.1503938687379--

.


Author: Curious <rmn100@gmail.com>
Date: Mon, 28 Aug 2017 11:14:03 -0700 (PDT)
Raw View
------=_Part_5076_330578662.1503944043493
Content-Type: multipart/alternative;
 boundary="----=_Part_5077_124583835.1503944043494"

------=_Part_5077_124583835.1503944043494
Content-Type: text/plain; charset="UTF-8"

@T. C, The is_decomposable trait has the same potential ODR issues as
std::iterator_traits.  But in retrospect, it's not critical to the proposal
of adding structured bindings to lambdas.  So maybe it's something that I
can just entirely leave out, and suggest addition later if this is a big
issue.

On Monday, 28 August 2017 09:44:47 UTC-7, Curious wrote:
>
> You are right.  This makes me wonder.  Are structured bindings not prone
> to the same problems?  The structured bindings decomposition checks to see
> if tuple_size<> is a complete type first, and then go on to check if the
> class can be decomposed via it's public members.  For example
>
> class Something {
> public:
>     int a;
> };
>
> namespace std {
> template <>
> class tuple_size<Something>;
> } // namespace std
>
> template <typename SomethingType>
> void foo(SomethingType something) {
>     auto [one] = something;
>     static_cast<void>(one);
> }
>
> void bar(Something something) {
>     foo(something);
> }
>
> /**
>  * Define the tuple shenanigans
>  */
> namespace std {
> template <>
> class tuple_size<Something> : std::integral_constant<int, 1> {};
> template <std::size_t Index>
> class tuple_element<Index, Something> {
>     using type = int;
> }
> template <std::size_t Index>
> int get(Something something) {
>     std::cout << "get(Something)" << std::endl;
>     return something.a;
> }
> } // namespace std
>
> void baz(Something something) {
>     // now expect logging
>     foo(something);
> }
>
> Although I suspect the above isn't an ODR problem because the bindings
> aren't involved in the template instantiation process.  Although it might
> be surprising to the user.
>
> I wonder why a simpler approach wasn't taken, why check for tuple_size<>
> to be a complete type rather than checking for the existence of a static
> constexpr value or a std::integral_constant<> typedef within the class?
>  This can now be a possible change, instead of allowing tuple_size<> to be
> specialized everywhere.  Make classes that want to pretend to be a tuple
> have a member typedef or a static constexpr and make tuple_size<> use that
> typedef in the general case, and don't leave the type undefined (I suspect
> this will break a lot of code, if people are checking to see if
> tuple_size<> is a complete type).  For example
>
> class TupleLike {
> public:
>     using tuple_size_type = std::integral_constant<int, 2>;
> private:
>     std::tuple<int, int> a;
> };
>
> This is much simpler and is not prone to ODR issues.  And now structured
> bindings can check for the existence of and inspect the tuple_size_type
> alias within the class.
>
> And then in the general case tuple_size<> can be defined like
>
> namespace std {
> template <typename T>
> class tuple_size {
>  static constexpr const auto value = T::tuple_size_type::value;
> };
>
> } // namespace std
>
> The second simpler solution to the is_decomposable problem is to not use
> the trait at all, and just let the lambda translate to an unconstrained
> template function in an anonymous class.
>
> Also, to illustrate my question about extent of the check, what should the
>> following code do? (This is basically GB 20's motivating example.)
>>
>
> Shouldn't this cause a hard error?  std::tuple_size is defined, and when
> the code tries to use it, it finds out that the specialization is just
> incorrectly defined.
>

--
You received this message because you are subscribed to the Google Groups "ISO C++ Standard - Future Proposals" group.
To unsubscribe from this group and stop receiving emails from it, send an email to std-proposals+unsubscribe@isocpp.org.
To post to this group, send email to std-proposals@isocpp.org.
To view this discussion on the web visit https://groups.google.com/a/isocpp.org/d/msgid/std-proposals/3509394f-e995-41d1-8fe0-3e7d8ecfe63e%40isocpp.org.

------=_Part_5077_124583835.1503944043494
Content-Type: text/html; charset="UTF-8"
Content-Transfer-Encoding: quoted-printable

<div dir=3D"ltr">@T. C, The <font face=3D"courier new, monospace">is_decomp=
osable</font> trait has the same potential ODR issues as <font face=3D"cour=
ier new, monospace">std::iterator_traits</font><font face=3D"arial, sans-se=
rif">. =C2=A0But in retrospect, it&#39;s not critical to the proposal of ad=
ding structured bindings to lambdas. =C2=A0So maybe it&#39;s something that=
 I can just entirely leave out, and suggest addition later if this is a big=
 issue.</font><div><font face=3D"arial, sans-serif"><br></font>On Monday, 2=
8 August 2017 09:44:47 UTC-7, Curious  wrote:<blockquote class=3D"gmail_quo=
te" style=3D"margin: 0;margin-left: 0.8ex;border-left: 1px #ccc solid;paddi=
ng-left: 1ex;"><div dir=3D"ltr">You are right. =C2=A0This makes me wonder. =
=C2=A0Are structured bindings not prone to the same problems? =C2=A0The str=
uctured bindings decomposition checks to see if <font face=3D"courier new, =
monospace">tuple_size&lt;&gt;</font> is a complete type first, and then go =
on to check if the class can be decomposed via it&#39;s public members. =C2=
=A0For example<div><br></div><div><div style=3D"background-color:rgb(250,25=
0,250);border:1px solid rgb(187,187,187);word-wrap:break-word"><code><div><=
span style=3D"color:#008">class</span><span style=3D"color:#000"> </span><s=
pan style=3D"color:#606">Something</span><span style=3D"color:#000"> </span=
><span style=3D"color:#660">{</span><span style=3D"color:#000"><br></span><=
span style=3D"color:#008">public</span><span style=3D"color:#660">:</span><=
span style=3D"color:#000"><br>=C2=A0 =C2=A0 </span><span style=3D"color:#00=
8">int</span><span style=3D"color:#000"> a</span><span style=3D"color:#660"=
>;</span><span style=3D"color:#000"><br></span><span style=3D"color:#660">}=
;</span><span style=3D"color:#000"><br><br></span><span style=3D"color:#008=
">namespace</span><span style=3D"color:#000"> std </span><span style=3D"col=
or:#660">{</span><span style=3D"color:#000"><br></span><span style=3D"color=
:#008">template</span><span style=3D"color:#000"> </span><span style=3D"col=
or:#660">&lt;&gt;</span><span style=3D"color:#000"><br></span><span style=
=3D"color:#008">class</span><span style=3D"color:#000"> tuple_size</span><s=
pan style=3D"color:#660">&lt;</span><span style=3D"color:#606">Something</s=
pan><span style=3D"color:#660">&gt;;</span><span style=3D"color:#000"><br><=
/span><span style=3D"color:#660">}</span><span style=3D"color:#000"> </span=
><span style=3D"color:#800">// namespace std</span><span style=3D"color:#00=
0"><br>=C2=A0 =C2=A0 <br></span><span style=3D"color:#008">template</span><=
span style=3D"color:#000"> </span><span style=3D"color:#660">&lt;</span><sp=
an style=3D"color:#008">typename</span><span style=3D"color:#000"> </span><=
span style=3D"color:#606">SomethingType</span><span style=3D"color:#660">&g=
t;</span><span style=3D"color:#000"><br></span><span style=3D"color:#008">v=
oid</span><span style=3D"color:#000"> foo</span><span style=3D"color:#660">=
(</span><span style=3D"color:#606">SomethingType</span><span style=3D"color=
:#000"> something</span><span style=3D"color:#660">)</span><span style=3D"c=
olor:#000"> </span><span style=3D"color:#660">{</span><span style=3D"color:=
#000"><br>=C2=A0 =C2=A0 </span><span style=3D"color:#008">auto</span><span =
style=3D"color:#000"> </span><span style=3D"color:#660">[</span><span style=
=3D"color:#000">one</span><span style=3D"color:#660">]</span><span style=3D=
"color:#000"> </span><span style=3D"color:#660">=3D</span><span style=3D"co=
lor:#000"> something</span><span style=3D"color:#660">;</span><span style=
=3D"color:#000"><br>=C2=A0 =C2=A0 </span><span style=3D"color:#008">static_=
cast</span><span style=3D"color:#080">&lt;void&gt;</span><span style=3D"col=
or:#660">(</span><span style=3D"color:#000">one</span><span style=3D"color:=
#660">);</span><span style=3D"color:#000"><br></span><span style=3D"color:#=
660">}</span><span style=3D"color:#000"><br><br></span><span style=3D"color=
:#008">void</span><span style=3D"color:#000"> bar</span><span style=3D"colo=
r:#660">(</span><span style=3D"color:#606">Something</span><span style=3D"c=
olor:#000"> something</span><span style=3D"color:#660">)</span><span style=
=3D"color:#000"> </span><span style=3D"color:#660">{</span><span style=3D"c=
olor:#000"><br>=C2=A0 =C2=A0 foo</span><span style=3D"color:#660">(</span><=
span style=3D"color:#000">something</span><span style=3D"color:#660">);</sp=
an><span style=3D"color:#000"><br></span><span style=3D"color:#660">}</span=
><span style=3D"color:#000"><br><br></span><span style=3D"color:#800">/**<b=
r>=C2=A0* Define the tuple </span><span style=3D"color:#800">shenanigans<br=
>=C2=A0*/</span><span style=3D"color:#000"><br></span><span style=3D"color:=
#008">namespace</span><span style=3D"color:#000"> std </span><span style=3D=
"color:#660">{</span><span style=3D"color:#000"><br></span><span style=3D"c=
olor:#008">template</span><span style=3D"color:#000"> </span><span style=3D=
"color:#660">&lt;&gt;</span><span style=3D"color:#000"><br></span><span sty=
le=3D"color:#008">class</span><span style=3D"color:#000"> tuple_size</span>=
<span style=3D"color:#660">&lt;</span><span style=3D"color:#606">Something<=
/span><span style=3D"color:#660">&gt;</span><span style=3D"color:#000"> </s=
pan><span style=3D"color:#660">:</span><span style=3D"color:#000"> std</spa=
n><span style=3D"color:#660">::</span><span style=3D"color:#000">integral_c=
onstant</span><span style=3D"color:#660">&lt;</span><span style=3D"color:#0=
08">int</span><span style=3D"color:#660">,</span><span style=3D"color:#000"=
> </span><span style=3D"color:#066">1</span><span style=3D"color:#660">&gt;=
</span><span style=3D"color:#000"> </span><span style=3D"color:#660">{};</s=
pan><span style=3D"color:#000"><br></span><span style=3D"color:#008">templa=
te</span><span style=3D"color:#000"> </span><span style=3D"color:#660">&lt;=
</span><span style=3D"color:#000">std</span><span style=3D"color:#660">::</=
span><span style=3D"color:#000">size_t </span><span style=3D"color:#606">In=
dex</span><span style=3D"color:#660">&gt;</span><span style=3D"color:#000">=
<br></span><span style=3D"color:#008">class</span><span style=3D"color:#000=
"> tuple_element</span><span style=3D"color:#660">&lt;</span><span style=3D=
"color:#606">Index</span><span style=3D"color:#660">,</span><span style=3D"=
color:#000"> </span><span style=3D"color:#606">Something</span><span style=
=3D"color:#660">&gt;</span><span style=3D"color:#000"> </span><span style=
=3D"color:#660">{</span><span style=3D"color:#000"><br>=C2=A0 =C2=A0 </span=
><span style=3D"color:#008">using</span><span style=3D"color:#000"> type </=
span><span style=3D"color:#660">=3D</span><span style=3D"color:#000"> </spa=
n><span style=3D"color:#008">int</span><span style=3D"color:#660">;</span><=
span style=3D"color:#000"><br></span><span style=3D"color:#660">}</span><sp=
an style=3D"color:#000"><br></span><span style=3D"color:#008">template</spa=
n><span style=3D"color:#000"> </span><span style=3D"color:#660">&lt;</span>=
<span style=3D"color:#000">std</span><span style=3D"color:#660">::</span><s=
pan style=3D"color:#000">size_t </span><span style=3D"color:#606">Index</sp=
an><span style=3D"color:#660">&gt;</span><span style=3D"color:#000"><br></s=
pan><span style=3D"color:#008">int</span><span style=3D"color:#000"> </span=
><span style=3D"color:#008">get</span><span style=3D"color:#660">(</span><s=
pan style=3D"color:#606">Something</span><span style=3D"color:#000"> someth=
ing</span><span style=3D"color:#660">)</span><span style=3D"color:#000"> </=
span><span style=3D"color:#660">{</span><span style=3D"color:#000"><br>=C2=
=A0 =C2=A0 std</span><span style=3D"color:#660">::</span><span style=3D"col=
or:#000">cout </span><span style=3D"color:#660">&lt;&lt;</span><span style=
=3D"color:#000"> </span><span style=3D"color:#080">&quot;get(Something)&quo=
t;</span><span style=3D"color:#000"> </span><span style=3D"color:#660">&lt;=
&lt;</span><span style=3D"color:#000"> std</span><span style=3D"color:#660"=
>::</span><span style=3D"color:#000">endl</span><span style=3D"color:#660">=
;</span><span style=3D"color:#000"><br>=C2=A0 =C2=A0 </span><span style=3D"=
color:#008">return</span><span style=3D"color:#000"> something</span><span =
style=3D"color:#660">.</span><span style=3D"color:#000">a</span><span style=
=3D"color:#660">;</span><span style=3D"color:#000"><br></span><span style=
=3D"color:#660">}</span><span style=3D"color:#000"><br></span><span style=
=3D"color:#660">}</span><span style=3D"color:#000"> </span><span style=3D"c=
olor:#800">// namespace std</span><span style=3D"color:#000"><br><br></span=
><span style=3D"color:#008">void</span><span style=3D"color:#000"> baz</spa=
n><span style=3D"color:#660">(</span><span style=3D"color:#606">Something</=
span><span style=3D"color:#000"> something</span><span style=3D"color:#660"=
>)</span><span style=3D"color:#000"> </span><span style=3D"color:#660">{</s=
pan><span style=3D"color:#000"><br>=C2=A0 =C2=A0 </span><span style=3D"colo=
r:#800">// now expect logging</span><span style=3D"color:#000"><br>=C2=A0 =
=C2=A0 foo</span><span style=3D"color:#660">(</span><span style=3D"color:#0=
00">something</span><span style=3D"color:#660">);</span><span style=3D"colo=
r:#000"><br></span><span style=3D"color:#660">}</span><span style=3D"color:=
#000"><br></span></div></code></div><div><br></div><div>Although I suspect =
the above isn&#39;t an ODR problem because the bindings aren&#39;t involved=
 in the template instantiation process. =C2=A0Although it might be surprisi=
ng to the user. =C2=A0</div><div><br></div><div>I wonder why a simpler appr=
oach wasn&#39;t taken, why check for tuple_size&lt;&gt; to be a complete ty=
pe rather than checking for the existence of a static constexpr value or a =
std::integral_constant&lt;&gt; typedef within the class? =C2=A0This can now=
 be a possible change, instead of allowing tuple_size&lt;&gt; to be special=
ized everywhere. =C2=A0Make classes that want to pretend to be a tuple have=
 a member typedef or a static constexpr and make tuple_size&lt;&gt; use tha=
t typedef in the general case, and don&#39;t leave the type undefined (I su=
spect this will break a lot of code, if people are checking to see if tuple=
_size&lt;&gt; is a complete type). =C2=A0For example</div><div><br></div><d=
iv style=3D"background-color:rgb(250,250,250);border:1px solid rgb(187,187,=
187);word-wrap:break-word"><code><div><span style=3D"color:#008">class</spa=
n><span style=3D"color:#000"> </span><span style=3D"color:#606">TupleLike</=
span><span style=3D"color:#000"> </span><span style=3D"color:#660">{</span>=
<span style=3D"color:#000"><br></span><span style=3D"color:#008">public</sp=
an><span style=3D"color:#660">:</span><span style=3D"color:#000"> =C2=A0<br=
>=C2=A0 =C2=A0 </span><span style=3D"color:#008">using</span><span style=3D=
"color:#000"> tuple_size_type </span><span style=3D"color:#660">=3D</span><=
span style=3D"color:#000"> std</span><span style=3D"color:#660">::</span><s=
pan style=3D"color:#000">integral_constant</span><span style=3D"color:#660"=
>&lt;</span><span style=3D"color:#008">int</span><span style=3D"color:#660"=
>,</span><span style=3D"color:#000"> </span><span style=3D"color:#066">2</s=
pan><span style=3D"color:#660">&gt;;</span><span style=3D"color:#000"><br><=
/span><span style=3D"color:#008">private</span><span style=3D"color:#660">:=
</span><span style=3D"color:#000"><br>=C2=A0 =C2=A0 std</span><span style=
=3D"color:#660">::</span><span style=3D"color:#000">tuple</span><span style=
=3D"color:#660">&lt;</span><span style=3D"color:#008">int</span><span style=
=3D"color:#660">,</span><span style=3D"color:#000"> </span><span style=3D"c=
olor:#008">int</span><span style=3D"color:#660">&gt;</span><span style=3D"c=
olor:#000"> a</span><span style=3D"color:#660">;</span><span style=3D"color=
:#000"><br></span><span style=3D"color:#660">};</span></div></code></div><d=
iv><br></div><div>This is much simpler and is not prone to ODR issues. =C2=
=A0And now structured bindings can check for the existence of and inspect t=
he <font face=3D"courier new, monospace">tuple_size_type</font> alias withi=
n the class. =C2=A0</div><div><br></div><div>And then in the general case <=
font face=3D"courier new, monospace">tuple_size&lt;&gt;</font> can be defin=
ed like=C2=A0</div><div><br></div><div style=3D"background-color:rgb(250,25=
0,250);border:1px solid rgb(187,187,187);word-wrap:break-word"><code><div><=
span style=3D"color:#008">namespace</span><span style=3D"color:#000"> std <=
/span><span style=3D"color:#660">{</span><span style=3D"color:#000"><br></s=
pan><span style=3D"color:#008">template</span><span style=3D"color:#000"> <=
/span><span style=3D"color:#660">&lt;</span><span style=3D"color:#008">type=
name</span><span style=3D"color:#000"> T</span><span style=3D"color:#660">&=
gt;</span><span style=3D"color:#000"><br></span><span style=3D"color:#008">=
class</span><span style=3D"color:#000"> tuple_size </span><span style=3D"co=
lor:#660">{</span><span style=3D"color:#000"><br>=C2=A0</span><span style=
=3D"color:#008">static</span><span style=3D"color:#000"> </span><span style=
=3D"color:#008">constexpr</span><span style=3D"color:#000"> </span><span st=
yle=3D"color:#008">const</span><span style=3D"color:#000"> </span><span sty=
le=3D"color:#008">auto</span><span style=3D"color:#000"> value </span><span=
 style=3D"color:#660">=3D</span><span style=3D"color:#000"> T</span><span s=
tyle=3D"color:#660">::</span><span style=3D"color:#000">tuple_size_type</sp=
an><span style=3D"color:#660">::</span><span style=3D"color:#000">value</sp=
an><span style=3D"color:#660">;</span><span style=3D"color:#000"><br></span=
><span style=3D"color:#660">};</span><span style=3D"color:#000"><br><br></s=
pan><span style=3D"color:#660">}</span><span style=3D"color:#000"> </span><=
span style=3D"color:#800">// namespace std</span><span style=3D"color:#000"=
><br></span></div></code></div><div><br>The second simpler solution to the =
<font face=3D"courier new, monospace">is_decomposable</font> problem is to =
not use the trait at all, and just let the lambda translate to an unconstra=
ined template function in an anonymous class.</div><div><br></div><blockquo=
te class=3D"gmail_quote" style=3D"margin:0;margin-left:0.8ex;border-left:1p=
x #ccc solid;padding-left:1ex"><div dir=3D"ltr"><div>Also, to illustrate my=
 question about extent of the check, what should the following code do? (Th=
is is basically GB 20&#39;s motivating example.)</div></div></blockquote><d=
iv><br></div><div>Shouldn&#39;t this cause a hard error? =C2=A0<font face=
=3D"courier new, monospace">std::tuple_size</font> is defined, and when the=
 code tries to use it, it finds out that the specialization is just incorre=
ctly defined.</div></div></div></blockquote></div></div>

<p></p>

-- <br />
You received this message because you are subscribed to the Google Groups &=
quot;ISO C++ Standard - Future Proposals&quot; group.<br />
To unsubscribe from this group and stop receiving emails from it, send an e=
mail to <a href=3D"mailto:std-proposals+unsubscribe@isocpp.org">std-proposa=
ls+unsubscribe@isocpp.org</a>.<br />
To post to this group, send email to <a href=3D"mailto:std-proposals@isocpp=
..org">std-proposals@isocpp.org</a>.<br />
To view this discussion on the web visit <a href=3D"https://groups.google.c=
om/a/isocpp.org/d/msgid/std-proposals/3509394f-e995-41d1-8fe0-3e7d8ecfe63e%=
40isocpp.org?utm_medium=3Demail&utm_source=3Dfooter">https://groups.google.=
com/a/isocpp.org/d/msgid/std-proposals/3509394f-e995-41d1-8fe0-3e7d8ecfe63e=
%40isocpp.org</a>.<br />

------=_Part_5077_124583835.1503944043494--

------=_Part_5076_330578662.1503944043493--

.


Author: "T. C." <rs2740@gmail.com>
Date: Mon, 28 Aug 2017 11:19:29 -0700 (PDT)
Raw View
------=_Part_7130_1076253472.1503944369355
Content-Type: multipart/alternative;
 boundary="----=_Part_7131_488310987.1503944369355"

------=_Part_7131_488310987.1503944369355
Content-Type: text/plain; charset="UTF-8"


On Monday, August 28, 2017 at 2:14:03 PM UTC-4, Curious wrote:
>
> @T. C, The is_decomposable trait has the same potential ODR issues as
> std::iterator_traits.
>

It doesn't. Instantiating iterator_traits<T> will always give you the same
definition if T is complete. And instantiating standard library templates
with incomplete types is generally prohibited.

is_decomposable, OTOH, does not have the luxury of ignoring incomplete
tuple_size<X>s.


--
You received this message because you are subscribed to the Google Groups "ISO C++ Standard - Future Proposals" group.
To unsubscribe from this group and stop receiving emails from it, send an email to std-proposals+unsubscribe@isocpp.org.
To post to this group, send email to std-proposals@isocpp.org.
To view this discussion on the web visit https://groups.google.com/a/isocpp.org/d/msgid/std-proposals/27932a56-329e-4854-8d6f-e8a4812adadb%40isocpp.org.

------=_Part_7131_488310987.1503944369355
Content-Type: text/html; charset="UTF-8"
Content-Transfer-Encoding: quoted-printable

<div dir=3D"ltr"><br>On Monday, August 28, 2017 at 2:14:03 PM UTC-4, Curiou=
s wrote:<blockquote class=3D"gmail_quote" style=3D"margin: 0;margin-left: 0=
..8ex;border-left: 1px #ccc solid;padding-left: 1ex;"><div dir=3D"ltr">@T. C=
, The <font face=3D"courier new, monospace">is_decomposable</font> trait ha=
s the same potential ODR issues as <font face=3D"courier new, monospace">st=
d::iterator_traits</font><font face=3D"arial, sans-serif">.</font></div></b=
lockquote><div><br></div><div>It doesn&#39;t. Instantiating iterator_traits=
&lt;T&gt; will always give you the same definition if T is complete. And in=
stantiating standard library templates with incomplete types is generally p=
rohibited.=C2=A0</div><div><br></div><div>is_decomposable, OTOH, does not h=
ave the luxury of ignoring incomplete tuple_size&lt;X&gt;s.</div><div><br><=
/div><div><br></div></div>

<p></p>

-- <br />
You received this message because you are subscribed to the Google Groups &=
quot;ISO C++ Standard - Future Proposals&quot; group.<br />
To unsubscribe from this group and stop receiving emails from it, send an e=
mail to <a href=3D"mailto:std-proposals+unsubscribe@isocpp.org">std-proposa=
ls+unsubscribe@isocpp.org</a>.<br />
To post to this group, send email to <a href=3D"mailto:std-proposals@isocpp=
..org">std-proposals@isocpp.org</a>.<br />
To view this discussion on the web visit <a href=3D"https://groups.google.c=
om/a/isocpp.org/d/msgid/std-proposals/27932a56-329e-4854-8d6f-e8a4812adadb%=
40isocpp.org?utm_medium=3Demail&utm_source=3Dfooter">https://groups.google.=
com/a/isocpp.org/d/msgid/std-proposals/27932a56-329e-4854-8d6f-e8a4812adadb=
%40isocpp.org</a>.<br />

------=_Part_7131_488310987.1503944369355--

------=_Part_7130_1076253472.1503944369355--

.


Author: Curious <rmn100@gmail.com>
Date: Mon, 28 Aug 2017 12:20:29 -0700 (PDT)
Raw View
------=_Part_7146_1600220776.1503948029651
Content-Type: multipart/alternative;
 boundary="----=_Part_7147_688418426.1503948029651"

------=_Part_7147_688418426.1503948029651
Content-Type: text/plain; charset="UTF-8"

I think I wasn't clear.  It is prone to ODR violations not neccesarily the
same way as is_decomposable would be but like the following

class Something {
public:
    using iterator_category = int;
    using difference_type = int;
    using pointer = int*;
    using value_type = int;
    using reference = int&;
};


void foo(Something) {
    auto iter_traits = std::iterator_traits<Something>{};
    static_cast<void>(iter_traits);
}

And then in another cpp file, which has the definition of Something visible

namespace std {
template <>
class iterator_traits<Something> {
public:
    using iterator_category = int;
    using difference_type = std::size_t;
    using pointer = int*;
    using value_type = int;
    using reference = int&;
};
} // namespace std


void bar(Something) {
    auto iter_traits = std::iterator_traits<Something>{};
    static_cast<void>(iter_traits);
}

Would it be best to just exclude is_decomposable from the proposal?  Is
there any other way to achieve the ability it provides to the
instantiations of the lambda?

On Monday, 28 August 2017 11:19:29 UTC-7, T. C. wrote:
>
>
> On Monday, August 28, 2017 at 2:14:03 PM UTC-4, Curious wrote:
>>
>> @T. C, The is_decomposable trait has the same potential ODR issues as
>> std::iterator_traits.
>>
>
> It doesn't. Instantiating iterator_traits<T> will always give you the same
> definition if T is complete. And instantiating standard library templates
> with incomplete types is generally prohibited.
>
> is_decomposable, OTOH, does not have the luxury of ignoring incomplete
> tuple_size<X>s.
>
>
>

--
You received this message because you are subscribed to the Google Groups "ISO C++ Standard - Future Proposals" group.
To unsubscribe from this group and stop receiving emails from it, send an email to std-proposals+unsubscribe@isocpp.org.
To post to this group, send email to std-proposals@isocpp.org.
To view this discussion on the web visit https://groups.google.com/a/isocpp.org/d/msgid/std-proposals/e148a17c-acc0-44a3-854b-531b13c0520d%40isocpp.org.

------=_Part_7147_688418426.1503948029651
Content-Type: text/html; charset="UTF-8"
Content-Transfer-Encoding: quoted-printable

<div dir=3D"ltr">I think I wasn&#39;t clear. =C2=A0It is prone to ODR viola=
tions not neccesarily the same way as is_decomposable would be but like the=
 following<div><br></div><div><div class=3D"prettyprint" style=3D"backgroun=
d-color: rgb(250, 250, 250); border: 1px solid rgb(187, 187, 187); word-wra=
p: break-word;"><code class=3D"prettyprint"><div class=3D"subprettyprint"><=
span style=3D"color: #008;" class=3D"styled-by-prettify">class</span><span =
style=3D"color: #000;" class=3D"styled-by-prettify"> </span><span style=3D"=
color: #606;" class=3D"styled-by-prettify">Something</span><span style=3D"c=
olor: #000;" class=3D"styled-by-prettify"> </span><span style=3D"color: #66=
0;" class=3D"styled-by-prettify">{</span><span style=3D"color: #000;" class=
=3D"styled-by-prettify"><br></span><span style=3D"color: #008;" class=3D"st=
yled-by-prettify">public</span><span style=3D"color: #660;" class=3D"styled=
-by-prettify">:</span><span style=3D"color: #000;" class=3D"styled-by-prett=
ify"><br>=C2=A0 =C2=A0 </span><span style=3D"color: #008;" class=3D"styled-=
by-prettify">using</span><span style=3D"color: #000;" class=3D"styled-by-pr=
ettify"> iterator_category </span><span style=3D"color: #660;" class=3D"sty=
led-by-prettify">=3D</span><span style=3D"color: #000;" class=3D"styled-by-=
prettify"> </span><span style=3D"color: #008;" class=3D"styled-by-prettify"=
>int</span><span style=3D"color: #660;" class=3D"styled-by-prettify">;</spa=
n><span style=3D"color: #000;" class=3D"styled-by-prettify"><br>=C2=A0 =C2=
=A0 </span><span style=3D"color: #008;" class=3D"styled-by-prettify">using<=
/span><span style=3D"color: #000;" class=3D"styled-by-prettify"> difference=
_type </span><span style=3D"color: #660;" class=3D"styled-by-prettify">=3D<=
/span><span style=3D"color: #000;" class=3D"styled-by-prettify"> </span><sp=
an style=3D"color: #008;" class=3D"styled-by-prettify">int</span><span styl=
e=3D"color: #660;" class=3D"styled-by-prettify">;</span><span style=3D"colo=
r: #000;" class=3D"styled-by-prettify"><br>=C2=A0 =C2=A0 </span><span style=
=3D"color: #008;" class=3D"styled-by-prettify">using</span><span style=3D"c=
olor: #000;" class=3D"styled-by-prettify"> pointer </span><span style=3D"co=
lor: #660;" class=3D"styled-by-prettify">=3D</span><span style=3D"color: #0=
00;" class=3D"styled-by-prettify"> </span><span style=3D"color: #008;" clas=
s=3D"styled-by-prettify">int</span><span style=3D"color: #660;" class=3D"st=
yled-by-prettify">*;</span><span style=3D"color: #000;" class=3D"styled-by-=
prettify"><br>=C2=A0 =C2=A0 </span><span style=3D"color: #008;" class=3D"st=
yled-by-prettify">using</span><span style=3D"color: #000;" class=3D"styled-=
by-prettify"> value_type </span><span style=3D"color: #660;" class=3D"style=
d-by-prettify">=3D</span><span style=3D"color: #000;" class=3D"styled-by-pr=
ettify"> </span><span style=3D"color: #008;" class=3D"styled-by-prettify">i=
nt</span><span style=3D"color: #660;" class=3D"styled-by-prettify">;</span>=
<span style=3D"color: #000;" class=3D"styled-by-prettify"><br>=C2=A0 =C2=A0=
 </span><span style=3D"color: #008;" class=3D"styled-by-prettify">using</sp=
an><span style=3D"color: #000;" class=3D"styled-by-prettify"> reference </s=
pan><span style=3D"color: #660;" class=3D"styled-by-prettify">=3D</span><sp=
an style=3D"color: #000;" class=3D"styled-by-prettify"> </span><span style=
=3D"color: #008;" class=3D"styled-by-prettify">int</span><span style=3D"col=
or: #660;" class=3D"styled-by-prettify">&amp;;</span><span style=3D"color: =
#000;" class=3D"styled-by-prettify"><br></span><span style=3D"color: #660;"=
 class=3D"styled-by-prettify">};</span><span style=3D"color: #000;" class=
=3D"styled-by-prettify"><br><br><br></span><span style=3D"color: #008;" cla=
ss=3D"styled-by-prettify">void</span><span style=3D"color: #000;" class=3D"=
styled-by-prettify"> foo</span><span style=3D"color: #660;" class=3D"styled=
-by-prettify">(</span><span style=3D"color: #606;" class=3D"styled-by-prett=
ify">Something</span><span style=3D"color: #660;" class=3D"styled-by-pretti=
fy">)</span><span style=3D"color: #000;" class=3D"styled-by-prettify"> </sp=
an><span style=3D"color: #660;" class=3D"styled-by-prettify">{</span><span =
style=3D"color: #000;" class=3D"styled-by-prettify"><br>=C2=A0 =C2=A0 </spa=
n><span style=3D"color: #008;" class=3D"styled-by-prettify">auto</span><spa=
n style=3D"color: #000;" class=3D"styled-by-prettify"> iter_traits </span><=
span style=3D"color: #660;" class=3D"styled-by-prettify">=3D</span><span st=
yle=3D"color: #000;" class=3D"styled-by-prettify"> std</span><span style=3D=
"color: #660;" class=3D"styled-by-prettify">::</span><span style=3D"color: =
#000;" class=3D"styled-by-prettify">iterator_traits</span><span style=3D"co=
lor: #660;" class=3D"styled-by-prettify">&lt;</span><span style=3D"color: #=
606;" class=3D"styled-by-prettify">Something</span><span style=3D"color: #6=
60;" class=3D"styled-by-prettify">&gt;{};</span><span style=3D"color: #000;=
" class=3D"styled-by-prettify"><br>=C2=A0 =C2=A0 </span><span style=3D"colo=
r: #008;" class=3D"styled-by-prettify">static_cast</span><span style=3D"col=
or: #080;" class=3D"styled-by-prettify">&lt;void&gt;</span><span style=3D"c=
olor: #660;" class=3D"styled-by-prettify">(</span><span style=3D"color: #00=
0;" class=3D"styled-by-prettify">iter_traits</span><span style=3D"color: #6=
60;" class=3D"styled-by-prettify">);</span><span style=3D"color: #000;" cla=
ss=3D"styled-by-prettify"><br></span><span style=3D"color: #660;" class=3D"=
styled-by-prettify">}</span></div></code></div><br>And then in another cpp =
file, which has the definition of <font face=3D"courier new, monospace">Som=
ething</font> visible<br><br><div class=3D"prettyprint" style=3D"background=
-color: rgb(250, 250, 250); border: 1px solid rgb(187, 187, 187); word-wrap=
: break-word;"><code class=3D"prettyprint"><div class=3D"subprettyprint"><s=
pan style=3D"color: #008;" class=3D"styled-by-prettify">namespace</span><sp=
an style=3D"color: #000;" class=3D"styled-by-prettify"> std </span><span st=
yle=3D"color: #660;" class=3D"styled-by-prettify">{</span><span style=3D"co=
lor: #000;" class=3D"styled-by-prettify"><br></span><span style=3D"color: #=
008;" class=3D"styled-by-prettify">template</span><span style=3D"color: #00=
0;" class=3D"styled-by-prettify"> </span><span style=3D"color: #660;" class=
=3D"styled-by-prettify">&lt;&gt;</span><span style=3D"color: #000;" class=
=3D"styled-by-prettify"><br></span><span style=3D"color: #008;" class=3D"st=
yled-by-prettify">class</span><span style=3D"color: #000;" class=3D"styled-=
by-prettify"> iterator_traits</span><span style=3D"color: #660;" class=3D"s=
tyled-by-prettify">&lt;</span><span style=3D"color: #606;" class=3D"styled-=
by-prettify">Something</span><span style=3D"color: #660;" class=3D"styled-b=
y-prettify">&gt;</span><span style=3D"color: #000;" class=3D"styled-by-pret=
tify"> </span><span style=3D"color: #660;" class=3D"styled-by-prettify">{</=
span><span style=3D"color: #000;" class=3D"styled-by-prettify"><br></span><=
span style=3D"color: #008;" class=3D"styled-by-prettify">public</span><span=
 style=3D"color: #660;" class=3D"styled-by-prettify">:</span><span style=3D=
"color: #000;" class=3D"styled-by-prettify"><br>=C2=A0 =C2=A0 </span><span =
style=3D"color: #008;" class=3D"styled-by-prettify">using</span><span style=
=3D"color: #000;" class=3D"styled-by-prettify"> iterator_category </span><s=
pan style=3D"color: #660;" class=3D"styled-by-prettify">=3D</span><span sty=
le=3D"color: #000;" class=3D"styled-by-prettify"> </span><span style=3D"col=
or: #008;" class=3D"styled-by-prettify">int</span><span style=3D"color: #66=
0;" class=3D"styled-by-prettify">;</span><span style=3D"color: #000;" class=
=3D"styled-by-prettify"><br>=C2=A0 =C2=A0 </span><span style=3D"color: #008=
;" class=3D"styled-by-prettify">using</span><span style=3D"color: #000;" cl=
ass=3D"styled-by-prettify"> difference_type </span><span style=3D"color: #6=
60;" class=3D"styled-by-prettify">=3D</span><span style=3D"color: #000;" cl=
ass=3D"styled-by-prettify"> std</span><span style=3D"color: #660;" class=3D=
"styled-by-prettify">::</span><span style=3D"color: #000;" class=3D"styled-=
by-prettify">size_t</span><span style=3D"color: #660;" class=3D"styled-by-p=
rettify">;</span><span style=3D"color: #000;" class=3D"styled-by-prettify">=
<br>=C2=A0 =C2=A0 </span><span style=3D"color: #008;" class=3D"styled-by-pr=
ettify">using</span><span style=3D"color: #000;" class=3D"styled-by-prettif=
y"> pointer </span><span style=3D"color: #660;" class=3D"styled-by-prettify=
">=3D</span><span style=3D"color: #000;" class=3D"styled-by-prettify"> </sp=
an><span style=3D"color: #008;" class=3D"styled-by-prettify">int</span><spa=
n style=3D"color: #660;" class=3D"styled-by-prettify">*;</span><span style=
=3D"color: #000;" class=3D"styled-by-prettify"><br>=C2=A0 =C2=A0 </span><sp=
an style=3D"color: #008;" class=3D"styled-by-prettify">using</span><span st=
yle=3D"color: #000;" class=3D"styled-by-prettify"> value_type </span><span =
style=3D"color: #660;" class=3D"styled-by-prettify">=3D</span><span style=
=3D"color: #000;" class=3D"styled-by-prettify"> </span><span style=3D"color=
: #008;" class=3D"styled-by-prettify">int</span><span style=3D"color: #660;=
" class=3D"styled-by-prettify">;</span><span style=3D"color: #000;" class=
=3D"styled-by-prettify"><br>=C2=A0 =C2=A0 </span><span style=3D"color: #008=
;" class=3D"styled-by-prettify">using</span><span style=3D"color: #000;" cl=
ass=3D"styled-by-prettify"> reference </span><span style=3D"color: #660;" c=
lass=3D"styled-by-prettify">=3D</span><span style=3D"color: #000;" class=3D=
"styled-by-prettify"> </span><span style=3D"color: #008;" class=3D"styled-b=
y-prettify">int</span><span style=3D"color: #660;" class=3D"styled-by-prett=
ify">&amp;;</span><span style=3D"color: #000;" class=3D"styled-by-prettify"=
><br></span><span style=3D"color: #660;" class=3D"styled-by-prettify">};</s=
pan><span style=3D"color: #000;" class=3D"styled-by-prettify"><br></span><s=
pan style=3D"color: #660;" class=3D"styled-by-prettify">}</span><span style=
=3D"color: #000;" class=3D"styled-by-prettify"> </span><span style=3D"color=
: #800;" class=3D"styled-by-prettify">// namespace std</span><span style=3D=
"color: #000;" class=3D"styled-by-prettify"><br><br><br></span><span style=
=3D"color: #008;" class=3D"styled-by-prettify">void</span><span style=3D"co=
lor: #000;" class=3D"styled-by-prettify"> bar</span><span style=3D"color: #=
660;" class=3D"styled-by-prettify">(</span><span style=3D"color: #606;" cla=
ss=3D"styled-by-prettify">Something</span><span style=3D"color: #660;" clas=
s=3D"styled-by-prettify">)</span><span style=3D"color: #000;" class=3D"styl=
ed-by-prettify"> </span><span style=3D"color: #660;" class=3D"styled-by-pre=
ttify">{</span><span style=3D"color: #000;" class=3D"styled-by-prettify"><b=
r>=C2=A0 =C2=A0 </span><span style=3D"color: #008;" class=3D"styled-by-pret=
tify">auto</span><span style=3D"color: #000;" class=3D"styled-by-prettify">=
 iter_traits </span><span style=3D"color: #660;" class=3D"styled-by-prettif=
y">=3D</span><span style=3D"color: #000;" class=3D"styled-by-prettify"> std=
</span><span style=3D"color: #660;" class=3D"styled-by-prettify">::</span><=
span style=3D"color: #000;" class=3D"styled-by-prettify">iterator_traits</s=
pan><span style=3D"color: #660;" class=3D"styled-by-prettify">&lt;</span><s=
pan style=3D"color: #606;" class=3D"styled-by-prettify">Something</span><sp=
an style=3D"color: #660;" class=3D"styled-by-prettify">&gt;{};</span><span =
style=3D"color: #000;" class=3D"styled-by-prettify"><br>=C2=A0 =C2=A0 </spa=
n><span style=3D"color: #008;" class=3D"styled-by-prettify">static_cast</sp=
an><span style=3D"color: #080;" class=3D"styled-by-prettify">&lt;void&gt;</=
span><span style=3D"color: #660;" class=3D"styled-by-prettify">(</span><spa=
n style=3D"color: #000;" class=3D"styled-by-prettify">iter_traits</span><sp=
an style=3D"color: #660;" class=3D"styled-by-prettify">);</span><span style=
=3D"color: #000;" class=3D"styled-by-prettify"><br></span><span style=3D"co=
lor: #660;" class=3D"styled-by-prettify">}</span></div></code></div><br>Wou=
ld it be best to just exclude <font face=3D"courier new, monospace">is_deco=
mposable</font> from the proposal? =C2=A0Is there any other way to achieve =
the ability it provides to the instantiations of the lambda?<br><br>On Mond=
ay, 28 August 2017 11:19:29 UTC-7, T. C.  wrote:<blockquote class=3D"gmail_=
quote" style=3D"margin: 0;margin-left: 0.8ex;border-left: 1px #ccc solid;pa=
dding-left: 1ex;"><div dir=3D"ltr"><br>On Monday, August 28, 2017 at 2:14:0=
3 PM UTC-4, Curious wrote:<blockquote class=3D"gmail_quote" style=3D"margin=
:0;margin-left:0.8ex;border-left:1px #ccc solid;padding-left:1ex"><div dir=
=3D"ltr">@T. C, The <font face=3D"courier new, monospace">is_decomposable</=
font> trait has the same potential ODR issues as <font face=3D"courier new,=
 monospace">std::iterator_traits</font><font face=3D"arial, sans-serif">.</=
font></div></blockquote><div><br></div><div>It doesn&#39;t. Instantiating i=
terator_traits&lt;T&gt; will always give you the same definition if T is co=
mplete. And instantiating standard library templates with incomplete types =
is generally prohibited.=C2=A0</div><div><br></div><div>is_decomposable, OT=
OH, does not have the luxury of ignoring incomplete tuple_size&lt;X&gt;s.</=
div><div><br></div><div><br></div></div></blockquote></div></div>

<p></p>

-- <br />
You received this message because you are subscribed to the Google Groups &=
quot;ISO C++ Standard - Future Proposals&quot; group.<br />
To unsubscribe from this group and stop receiving emails from it, send an e=
mail to <a href=3D"mailto:std-proposals+unsubscribe@isocpp.org">std-proposa=
ls+unsubscribe@isocpp.org</a>.<br />
To post to this group, send email to <a href=3D"mailto:std-proposals@isocpp=
..org">std-proposals@isocpp.org</a>.<br />
To view this discussion on the web visit <a href=3D"https://groups.google.c=
om/a/isocpp.org/d/msgid/std-proposals/e148a17c-acc0-44a3-854b-531b13c0520d%=
40isocpp.org?utm_medium=3Demail&utm_source=3Dfooter">https://groups.google.=
com/a/isocpp.org/d/msgid/std-proposals/e148a17c-acc0-44a3-854b-531b13c0520d=
%40isocpp.org</a>.<br />

------=_Part_7147_688418426.1503948029651--

------=_Part_7146_1600220776.1503948029651--

.