Trip report: Winter 2021 ISO C++ standards meeting (virtual)

Today, the ISO C++ committee held its second full-committee (plenary) meeting of the pandemic and adopted a few more features and improvements for draft C++23.

A record of 18 voting nations sent representatives to this meeting: Austria, Bulgaria, Canada, Czech Republic, Finland, France, Germany, Israel, Italy, Japan, Netherlands, Poland, Romania, Russia, Spain, Switzerland, United Kingdom, and United States. Japan had participated in person during C++98 and C++11, and has always given us good remote ballot feedback during C++14/17/20, and is attending again now; welcome back! Italy and Romania are our newest national bodies; welcome!

Our virtual 2021

We continue to have the same priorities and the same schedule we originally adopted for C++23. However, since the pandemic began, WG21 and its subgroups have had to meet all-virtually via Zoom, and we are not going to try to have a face-to-face meeting in 2021 (see What’s Next below). Some subgroups had already been having virtual meetings for years, but this was a major change for other groups including our two main design groups – the language and library evolution working groups (EWG and LEWG). In all, over the past year we have held approximately 200 virtual meetings.

Today: A few more C++23 features adopted

Today we formally adopted a second round of small features for C++23, as well as a number of bug fixes. Below, I’ll list some of the more user-noticeable changes and credit all those paper authors, but note that this is far from an exhaustive list of important contributors… even for these papers, nothing gets done without help from a lot of people and unsung heroes, so thank you first to all of the people not named here who helped the authors move their proposals forward! And thank you to everyone who worked on the adopted issue resolutions and smaller papers I didn’t include in this list.

P1102 by Alex Christensen and JF Bastien is the main noticeable change we adopted for the core language itself. It’s just a tiny bit of cleanup, but one that I’m personally fond of: In C++23 we will be able to omit empty ( ) lambda parameter lists even when we have to declare the lambda mutable. I’m the one who proposed the lambda syntax we have today (except for the mutable part which wasn’t mine and I never liked), including that it enabled making unused parts of the syntax optional so that we can write simple lambdas simply. For example, today we can already write

[x]{ return f(x); }

as a legal synonym for

[x] () -> auto { return f(x); }

and omit the empty parameter list and deduced return type. Even so, I’ve noticed a lot of people write the ( ) part anyway, which isn’t wrong or anything, it’s just that often they write it because they don’t know they can omit it too. And part of the problem was the oddity in pre-C++23 that if you need to write mutable, then you actually do have to also write the ( ) (but not the return type), which was just weird but was another reason for people to just write ( ) all the time, because sometimes they had to. With P1102, we don’t have to. That’s more consistent. Thanks, Alex and JF!

In the spirit of “completing C++20,” P2259 by Tim Song makes several fixes to iterator_category to make it work better with ranges and adaptors. Here is an example of code that does not compile today for arcane reasons (see the paper), but will be legal C++23 thanks to Tim:

std::vector<int> vec = {42};
auto r = vec | std::views::transform([](int c) { return std::views::single(c);})
             | std::views::join
             | std::views::filter([](int c) { return c > 0; });
r.begin();

Further in the “completing C++20” spirit, P2017 by Barry Revzin fixes some additional glitches in ranges to make them work better. Here is an example of safe and efficient code that does not compile today, where for arcane reasons the declaration of e isn’t supported and today’s workaround is to make the code more complex and less efficient. This will be legal C++23 thanks to Barry:

auto trim(std::string const& s) {
    auto isalpha = [](unsigned char c){ return std::isalpha(c); };
    auto b = ranges::find_if(s, isalpha);
    auto e = ranges::find_if(s | views::reverse, isalpha).base();
    return subrange(b, e);
}

P2212 by Alexey Dmitriev and Howard Hinnant generalizes time_point::clock to allow for greater flexibility in the kinds of clocks it supports, including stateful clocks, external system clocks that don’t really have time_points, representing “time of day” as a distinct time_point, and more.

P2162 by Barry Revzin takes an important first step toward cleaning up std::visit and lay the groundwork for its further generalization. Even if you don’t yet love std::visit, it’s a useful tool that P2162 makes more useful by making it work more regularly. We expect to see further generalization in the future, which is much easier to do with a cleaner and more regular existing feature to build upon.

Finally, I saw cheers and celebratory emoji erupt in the Zoom chat window when we adopted P1682 by JeanHeyd Meneide. It’s very small, but very useful. When passing an enum to an API that uses the underlying type, today we have to write a static_cast to the std::underlying_type, which makes us repeat the enum’s name and so is cumbersome all the time and brittle for type-safety under maintenance if we change to use a different enum:

some_untyped_api( static_cast<std::underlying_type_t<ABCD>>(some_value) );

Thanks to JeanHeyd, in C++23 we will be able to write:

some_untyped_api( std::to_underlying(some_value) );

Note that of course standard library vendors don’t have to wait until 2023 to provide to_underlying or any of these other fixes and improvements. Just having a feature like this one voted into the draft standard is often enough for vendors to be proactive in providing it… these days, vendors are more closely tracking our draft standard meeting by meeting rather than waiting for the official release, in part because we are shipping regularly and predictably and we don’t vote features into the draft standard until we think they’re pretty well baked so that vendors have less risk in implementing them early.

We also adopted a number of other issue resolutions and small papers that made additional improvements.

Finally, we came close to adopting P0533 by Edward Rosten and Oliver Rosten, which is about adding constexpr to many of the functions in math.h that we share with C. This is clearly a Good Thing and therefore many voted in favor of adopting the paper. The only hesitation that stopped it from getting consensus this time were concerns that it needed more time to iron out how implementations would implement it, such as how to deal with errno in a constexpr context. This is the kind of question that often arises when we want to make improvements to entities declare in the C headers, because not only are they governed by the C standard rather than the C++ standard, but typically they are provided and controlled by the operating system vendor rather than by the C++ compiler/library writer, and those constraints always mean a bit of extra work when we want to make improvements for C++ programmers and remain compatible. As far as I know, everyone wants to see these functions made constexpr, so we expect to see this paper come to plenary again in the future. Thanks for your perseverance, Edward and Oliver!

What’s next

As long as we are meeting virtually, we will continue to have virtual plenaries like the one we had this week to formally adopt new features as they progress through subgroups. Our next two virtual plenaries to adopt features into the C++23 working draft will be held in June and November. Progress will be slower than when we can meet face-to-face, and we’ll doubtless defer some topics that really need in-person discussion until we can meet again safely, but in the meantime we’ll make what progress we can and we’ll ship C++23 on time.

The next tentatively planned face-to-face meeting is February 2022 in Portland, OR, USA; however, we likely won’t know until well into the autumn whether we’ll be able to confirm that or need to postpone it. You can find a list of our meeting plans on the Upcoming Meetings page.

Thank you again to the hundreds of people who are working tirelessly on C++, even in our current altered world. Your flexibility and willingness to adjust are much appreciated by all of us in the committee and by all the C++ communities! Thank you, and see you on Zoom.

GotW #100: Preconditions, Part 1 (Difficulty: 8/10)

This special Guru of the Week series focuses on contracts. We’ve seen how postconditions are directly related to assertions (see GotWs #97 and #99). So are preconditions, but that in one important way makes them fundamentally different. What is that? And why would having language support benefit us even more for writing preconditions more than for the other two?

JG Question

1. What is a precondition, and how is it related to an assertion? Explain your answer using the following example, which uses a variation of a proposed post-C++20 syntax for preconditions. [1]

// A precondition along the lines proposed in [1]

void f( int min, int max )
    [[pre( min <= max )]]
{
    // ...
}

Guru Questions

2. Rewrite the example in Question 1 to show how to approximate the same effect using assertions in today’s C++. Are there any drawbacks to your solution compared to having language support for preconditions?

3. If a precondition fails, what does that indicate, and who is responsible for fixing the failure? Explain how this makes a precondition fundamentally different from every other kind of contract.

4. Consider this example, expanded from a suggestion by Gábor Horváth:

auto calc( std::vector<int> const&  x ,
           std::floating_point auto y ) -> double
    [[pre( x[0] <= std::sqrt(y) )]] ;

Note that std::floating_point is a C++20 concept.

  • What kinds of preconditions must a caller of calc satisfy that can’t generally be written as testable boolean expressions?
  • What kinds of boolean-testable preconditions are implicit within the explicitly written declaration of calc?
  • Should any of these boolean-testable implicit preconditions also be written explicitly here in this precondition code? Explain.

Notes

[1] G. Dos Reis, J. D. Garcia, J. Lakos, A. Meredith, N. Myers, and B. Stroustrup. “P0542: Support for contract based programming in C++” (WG21 paper, June 2018). Subsequent EWG discussion favored changing “expects” to “pre” and “ensures” to “post,” and to keep it as legal compilable (if unenforced) C++20 for this article I also modified the syntax from : to ( ). That’s not a statement of preference, it’s just so the examples can compile today to make them easier to check.

GotW #99 Solution: Postconditions (Difficulty: 7/10)

This special Guru of the Week series focuses on contracts. Postconditions are directly related to assertions (see GotW #97)… but how, exactly? And since we can already write postconditions using assertions, why would having language support benefit us more for writing postconditions more than for writing (ordinary) assertions?

1. What is a postcondition, and how is it related to an assertion?

A function’s postconditions document “what it does” — they assert the function’s intended effects, including the return value and any other caller-visible side effects, which must hold at every return point when the function returns to the caller.

A postcondition IS-AN assertion in every way described in GotW #97, with the special addition that whereas a general assertion is always checked where it is written, a postcondition is written on the function and checked at every return (which could be multiple places). Otherwise, it’s “just an assertion”: As with an assertion, if a postcondition is false then it means there is a bug, likely right there inside the function on which the postcondition is written (or in the postcondition itself), because if prior contracts were well tested then likely this function created the first unexpected state. [2]

Explain your answer using the following example, which uses a variation of a proposed post-C++20 syntax for postconditions. [1]

// Example 1(a): A postcondition along the lines proposed in [1]

string combine_and_decorate( const string& x, const string& y )
    [[post( _return_.size() > x.size() + y.size() )]]
{
    if (x.empty()) {
        return "[missing] " + y + optional_suffix();
    } else {
        return x + ' ' + y + something_computed_from(x);
    }
}

The above would be roughly equivalent to writing the test before every return statement instead:

// Example 1(b): What a compiler might generate for Example 1(a)

string combine_and_decorate( const string& x, const string& y )
{
    if (x.empty()) {
        auto&& _return_ = "[missing] " + y + optional_suffix();
        assert( _return_.size() > x.size() + y.size() );
        return std::forward<decltype(_return_)>(_return_);
    } else {
        auto&& _return_ = x + ' ' + y + something_computed_from(x);
        assert( _return_.size() > x.size() + y.size() );
        return std::forward<decltype(_return_)>(_return_);
    }
}

2. Rewrite the example in Question 1 to show how to approximate the same effect using assertions in today’s C++. Are there any drawbacks to your solution compared to having language support for postconditions?

We could always write Example 1(b) by hand, but language support for postconditions is better in two key ways:

(A) The programmer should only write the condition once.

(B) The programmer should not need to write forwarding boilerplate by hand to make looking at the return value efficient.

How can we approximate those advantages?

Option 1 (basic): Named return object + an exit guard

The simplest way to achieve (A) would be to use the C-style goto exit; pattern:

// Example 2(a)(i): C-style “goto exit;” postcondition pattern

string combine_and_decorate( const string& x, const string& y )
{
    auto _return_ = string();
    if (x.empty()) {
        _return_ = "[missing] " + y + optional_suffix();
        goto post;
    } else {
        _return_ = x + ' ' + y + something_computed_from(x);
        goto post;
    }

post:
    assert( _return_.size() > x.size() + y.size() );
    return _return_;
}

If you were thinking, “in C++ this wants a scope guard,” you’re right! [3] Guards still need access to the return value, so the structure is basically similar:

// Example 2(a)(ii): scope_guard pattern, along the lines of [3]

string combine_and_decorate( const string& x, const string& y )
{
    auto _return_ = string();
    auto post = std::experimental::scope_success([&]{
        assert( _return_.size() > x.size() + y.size() );
    });

    if (x.empty()) {
        _return_ = "[missing] " + y + optional_suffix();
        return _return_;
    } else {
        _return_ = x + ' ' + y + something_computed_from(x);
        return _return_;
    }
}

Advantages:

  • Achieved (A). The programmer writes the condition only once.

Drawbacks:

  • Didn’t achieve (B). There’s no forwarding boilerplate, but only because we’re not even trying to forward…
  • Overhead (maybe). … and to look at the return values we require a named return value and a move assignment into that object, which is overhead if the function wasn’t already doing that.
  • Brittle. The programmer has to remember to convert every return site to _return_ = ...; goto post; or _return_ = ...; return _return_;… If they forget, the code silently compiles but doesn’t check the postcondition.

Option 2 (better): “return post” postcondition pattern

Here’s a second way to do it that achieves both goals, using a local function (which we have to write as a lambda in C++):

// Example 2(b): “return post” postcondition pattern

string combine_and_decorate( const string& x, const string& y )
{
    auto post = [&](auto&& _return_) -> auto&& {
        assert( _return_.size() > x.size() + y.size() );
        return std::forward<decltype(_return_)>(_return_);
    };

    if (x.empty()) {
        return post( x + ' ' + y + something_computed_from(x) );
    } else {
        return post( "[missing] " + y + optional_suffix() );
    }
}

Advantages:

  • Achieved (A). The programmer writes the condition only once.
  • Efficient. We can look at return values efficiently, without requiring a named return value and a move assignment.

Drawbacks:

  • Didn’t achieve (B). We still have to write the forwarding boilerplate, but at least it’s only in one place.
  • Brittle. The programmer has to remember to convert every return site to return post. If they forget, the code silently compiles but doesn’t check the postcondition.

Option 3 (mo’betta): Wrapping up option 2… with a macro

We can improve Option 2 by wrapping the boilerplate up in a macro (sorry). Note that instead of “MY_” you’d use your company’s preferred unique macro prefix: [4]

// Eliminate forward-boilerplate with a macro (written only once)
#define MY_POST(postconditions)                            \
    auto post = [&](auto&& _return_) -> auto&& {           \
        assert( postconditions );                          \
        return std::forward<decltype(_return_)>(_return_); \
    };

And then the programmer can just write:

// Example 2(c): “return post” with boilerplate inside a macro

string combine_and_decorate( const string& x, const string& y )
{   MY_POST( _return_.size() > x.size() + y.size() );

    if (x.empty()) {
        return post( x + ' ' + y + something_computed_from(x) );
    } else {
        return post( "[missing] " + y + optional_suffix() );
    }
}

Advantages:

  • Achieved (A) and (B). The programmer writes the condition only once, and doesn’t write the forwarding boilerplate.
  • Efficient. We can look at the return value without requiring a local variable for the return value, and without an extra move operation to put the value there.
  • Future-friendly. You may have noticed that I changed my usual brace style to write { MY_POST on a single line; that’s to make it easily replaceable with search-and-replace. If you systematically declare the condition as { MY_POST at the start of the function, and systematically write return post() to use it, the code is likely more future-proof — if we get language support for postconditions with a syntax like [1], migrating your code to that could be as simple as search-and-replace:

{ MY_POST( * )[[post _return_: * )]] {

return post( * )return *

Drawbacks:

  • (improved) Brittle. It’s still a manual pattern, but now we have the option of making it impossible for the programmer to forget return post by extending the macro to include a check that post was used before each return (see [5]). That’s feasible to put into the Option 3 macro, whereas it was not realistic to ask the programmer to write out by hand in Options 1 and 2.

GUIDELINE: If you don’t already use a way to write postconditions as code, consider trying something like MY_POST until language support is available. It’s legal C++ today, it’s not terrible, and it’s future-friendly to adopting future C++ language contracts.

Finally, all of these options share a common drawback:

  • Less composable/toolable. The next library or team will have THEIR_POST convention that’s different, which makes it hard to write tools to support both styles. Language support has an important incidental benefit of providing a common syntax that portable code and tools can rely upon.

3. Should a postcondition be expected to be true if the function throws an exception back to the caller?

No.

First, let’s generalize the question: Anytime you see “if the function throws an exception,” mentally rewrite it to “if the function reports that it couldn’t do what it advertised, namely complete its side effects.” That’s independent of whether it reports said failure using an exception, std::error_code, HRESULT, errno, or any other way.

Then the question answers itself: No, by definition. A postcondition documents the side effects, and if those weren’t achieved then there’s nothing to check. And for postconditions involving the return value we can add: No, those are meaningless by construction, because it doesn’t exist.

“But wait!” someone might interrupt. “Aren’t there still things that need to be true on function exit even if the function failed?” Yes, but those aren’t postconditions. Let’s take a look.

Justify your answer with example(s).

Consider this code:

// Example 3: (Not) a reasonable postcondition?

void append_and_decorate( string& x, string&& y )
    [[post( x.size() <= x.capacity() && /* other non-corruption */ )]]
{
    x += y + optional_suffix();
}

This can seem like a sensible “postcondition” even when an exception is thrown, but it is testing whether x is still a valid object of its type… and sure, that had better be true. But that’s an invariant, which should be written once on the type [2], not a postcondition to be laboriously repeated arbitrarily many times on every function that ever might touch an object of that type.

When reasoning about function failures, we use the well-known Abrahams error safety guarantees, and now it becomes important to understand them in terms of invariants:

  • The nofail guarantee is “the function cannot fail” (e.g., such functions should be noexcept), and so doesn’t apply here since we’re discussing what happens if the function does fail.
  • The basic guarantee is “no corruption,” every object we might have tried to modify is still a valid object of its type… but that’s identical to saying “the object still meets the invariants of its type.”
  • The strong guarantee is “all or nothing,” so in the case we’re talking about where an error is being reported, a strong guarantee function is again saying that all invariants hold. (It also says observable state did not change, but I’ll ignore that for now; for how we might want to check that, see [6].)

So we’re talking primarily about class invariants… and those should hold on both successful return and error exit, and they should be written on the type rather than on every function that uses the type.

GUIDELINE: If you’re trying to write a “postcondition” that should still be true even if an exception or other error is reported, you’re probably either trying to write an invariant instead [2], or trying to check the strong did-nothing guarantee [6].

4. Should postconditions be able to refer to both the initial (on entry) and final (on exit) value of a parameter, if those could be different?

Yes.

If so, give an example.

Consider this code, which uses a strawman _in_() syntax for referring to subexpressions of the postcondition that should be computed on entry so they can refer to the “in” value of the parameter (note: this was not proposed in [1]):

// Example 4(a): Consulting “in” state in a postcondition

void instrumented_push( vector<widget>& c, const widget& value )
    [[post( _in_(c.size())+1 == c.size() )]]
{

    c.push_back(value);

    // perform some extra work, such as logging which
    // values are added to which containers, then return
}

Postconditions like this one express relative side effects, where the “out” state is a delta from the “in” state of the parameter. To write postconditions like this one, we have to be able to refer to both states of the parameter, even for parameters that must be modifiable.

Note that this doesn’t require taking a copy of the parameter… that would be expensive for c! Rather, an implementation would just evaluate any _in_ subexpression on entry and store only that result as a temporary, then evaluate the rest of the expression on exist. For example, in this case the implementation could generate something like this:

// Example 4(b): What an implementation might generate for 4(a)

void instrumented_push( vector<widget>& c, const widget& value )
{
    auto __in_c_size = c.size();

    c.push_back(value);

    // perform some extra work, such as logging which
    // values are added to which containers, then return

    assert( __in_c_size+1 == c.size() );
}

Notes

[1] G. Dos Reis, J. D. Garcia, J. Lakos, A. Meredith, N. Myers, and B. Stroustrup. “P0542: Support for contract based programming in C++” (WG21 paper, June 2018). Subsequent EWG discussion favored changing “expects” to “pre” and “ensures” to “post,” and to keep it as legal compilable (if unenforced) C++20 for this article I also modified the syntax from : to ( ), and to name the return value _return_ for postconditions. That’s not a statement of preference, it’s just so the examples can compile today to make them easier to check.

[2] Upcoming GotWs will cover preconditions and invariants, including how invariants relate to postconditions.

[3] P. Sommerlad and A. L. Sandoval. “P0052: Generic Scope Guard and RAII Wrapper for the Standard Library” (WG21 paper, February 2019). Based on pioneering work by Andrei Alexandrescu and Petru Marginean starting with “Change the Way You Write Exception-Safe Code – Forever” (Dr. Dobb’s Journal, December 2000), and widely implemented in D and other languages, the Folly library, and more.

[4] In a real system we’d want a few more variations, such as:

// A separate _V version for functions that don’t return
// a value, because 'void' isn’t regular
#define MY_POST_V(postconditions)                          \
    auto post = [&]{ assert( postconditions ); };

// Parallel _DECL forms to work on forward declarations,
// for people who want to repeat the postcondition there
#define MY_POST_DECL(postconditions)   // intentionally empty 
#define MY_POST_V_DECL(postconditions) // intentionally empty

Note: We could try to combine MY_POST_V and MY_POST by always creating both a single-parameter lambda and a no-parameter lambda, and then “overloading” them using something like compose from Boost’s wonderful High-Order Function library by Paul Fultz II. Then in a void-returning function return post() still works fine even with empty parens. I didn’t do that because the proposed future in-language contracts proposed in [1] uses a slightly different syntax depending on whether there’s a return value, so if our syntax doesn’t somehow have such a distinction then it will be harder to migrate this macro to a syntax like [1] with a simple search-and-replace.

[5] We could add extra machinery help the programmer remember to write return post, so that just executing a return without post will assert… set a flag that gets sets on every post() evaluation, and then assert that flag in the destructor of an RAII object for every normal return. The code is pretty simple with a scope guard [3]:

// Check that the programmer wrote “return post” each time
#define MY_POST_CHECKED                                     \
    auto post_checked = false;                              \
    auto post_guard = std::experimental::scope_success([&]{ \
        assert( post_checked );                             \
    });

Then in MY_POST and MY_POST_V, pull in this machinery and then also set post_checked:

#define MY_POST(postconditions)                             \
    MY_POST_CHECKED                                         \
    auto post = [&](auto&& _return_) -> auto&& {            \
        assert( postconditions );                           \
        post_checked = true;                                \
        return std::forward<decltype(_return_)>(_return_);  \
    };

#define MY_POST_V(postconditions)                           \
    MY_POST_CHECKED                                         \
    auto post = [&]{                                        \
        assert( postconditions );                           \
        post_checked = true;                                \
    };

If you don’t have a scope guard helper, you can roll your own, where “successful exit” is detectable by seeing that the std::uncaught_exceptions() exception count hasn’t changed:

// Hand-rolled alternative if you don’t have a scope guard
#define MY_POST_CHECKED                                     \
    auto post_checked = false;                              \
    struct post_checked_ {                                  \
        const bool *pflag;                                  \
        const int  ecount = std::uncaught_exceptions();     \
        post_checked_(const bool* p) : pflag{p} {}          \
        ~post_checked_() {                                  \
            assert( *pflag ||                               \
                    ecount != std::uncaught_exceptions() ); \
        }                                                   \
    } post_checked_guard{&post_checked}; 

[6] For strong-guarantee functions, we could try to check that all observable state is the same as on function entry. In some cases, we can partly do that… for example, writing the test that a failed vector::push_back didn’t invalidate any pointers into the container may sound hard, but it’s actually the easy part of that function’s “error exit” condition! Using a strawman syntax like [1], extended to include an “error” exit condition:

// (Using a hypothetical “error exit” condition)
// This is enough to check that no pointers into *this are invalid

template <typename T, typename Allocator>
constexpr void vector<T>::push_back( const T& )
    [[error( _in_.data() == data() && _in_.size() == size() )]] ;

But other “error exit” checks for this same function would be hard, expensive, or impossible to express. For example, it would be expensive to write the check that all elements in the vector have their original values, which would require first taking a deep copy of the container.

Acknowledgments

Thank you to the following for their feedback on this material: Joshua Berne, Gábor Horváth, Andrzej Krzemieński, James Probert, Bjarne Stroustrup, Andrew Sutton.

GotW #99: Postconditions (Difficulty: 7/10)

This special Guru of the Week series focuses on contracts. Postconditions are directly related to assertions (see GotW #97)… but how, exactly? And since we can already write postconditions using assertions, why would having language support benefit us more for writing postconditions more than for writing (ordinary) assertions?

JG Question

1. What is a postcondition, and how is it related to an assertion? Explain your answer using the following example, which uses a variation of a proposed post-C++20 syntax for postconditions. [1]

// A postcondition along the lines proposed in [1]

string combine_and_decorate( const string& x, const string& y )
    [[post( _return_.size() > x.size() + y.size() )]]
{
    if (x.empty()) {
        return "[missing] " + y + optional_suffix();
    } else {
        return x + ' ' + y + something_computed_from(x);
    }
}

Guru Questions

2. Rewrite the example in Question 1 to show how to approximate the same effect using assertions in today’s C++. Are there any drawbacks to your solution compared to having language support for postconditions?

3. Should a postcondition be expected to be true if the function throws an exception back to the caller? Justify your answer with example(s).

4. Should a postcondition be able to refer to both the initial (on entry) and final (on exit) value of a parameter, if those could be different? If so, give an example.

Notes

[1] G. Dos Reis, J. D. Garcia, J. Lakos, A. Meredith, N. Myers, and B. Stroustrup. “P0542: Support for contract based programming in C++” (WG21 paper, June 2018). Subsequent EWG discussion favored changing “expects” to “pre” and “ensures” to “post,” and to keep it as legal compilable (if unenforced) C++20 for this article I also modified the syntax from : to ( ), and to name the return value _return_ for postconditions. That’s not a statement of preference, it’s just so the examples can compile today to make them easier to check.

GotW #98 Solution: Assertion levels (Difficulty: 5/10)

This special Guru of the Week series focuses on contracts. We covered basic assertions in GotW #97… but not all asserted conditions are created equal.

Given some assertion facility that can be used like this:

MyAssert( condition );  // expresses that ‘condition’ must be true

1. Give one example each of an asserted condition whose run-time evaluation is:

a) super cheap

Without resorting to constexpr expressions, it’s hard to find one cheaper than the one we saw in GotW #97 Example 3, which we can simplify down to this:

// Example 1(a): A dirt cheap assertion (from GotW #97 Example 3)

int min = /* some computation */;
int max = /* some other computation */;
MyAssert( min <= max );

This is always going to be dirt cheap. Not only is the integer comparison operation cheap, but min and max are already being accessed by this function and so they’re already “hot” in registers or cache.

b) arbitrarily expensive

“A condition that’s expensive? That sounds pretty easy,” you might say, and you’re right!

One commonly cited example is is_sorted. Just to emphasize how expensive it can be both in absolute terms and also relative to the program’s normal execution, let’s put it inside a well-known function… this is a precondition, but we’ll write it as an assertion in the function body for now which doesn’t affect this question: [1]

// Example 1(b): An arbitrarily expensive assertion

template <typename Iter, typename T>
bool binary_search( Iter begin, Iter end, const T& value ) {
    MyAssert( is_sorted(begin, end) );
    // ...
}

Checking that all the container’s elements are in ascending order requires visiting them all, and that O(N) linear complexity is arbitrarily expensive when the container’s size N can be arbitrarily large.

The icing on the cake: In this example, just evaluating the assertion requires doing more work than the entire function it appears in, which is only O(log N) complexity!

On a humorous note, O(N) remains O(N) no matter how hard we try to make it efficient:

MyAssert( std::is_sorted( std::execution::par, begin(s), end(s) ) );
                  // still O(N) arbitrarily expensive, but good try!

2. What does the answer to Question 1 imply for assertion checking? Explain.

We want a way to enable checking for some assertions but not others in the same code, because we may not always be able to afford expensive checks. That’s true whether we’re enabling checking at test time (e.g., on the developer’s machine) or at run time (e.g., in production).

Some conditions are so expensive that we may never check them without a good reason, even in testing. Example 1(b)’s is_sorted is a great example: You probably won’t ever enable it in production, and likely not by default in testing, except by explicitly turning it on during a bug hunt after enabling checking for cheaper assertions wasn’t enough or pointed at this data structure for deeper investigation. [2]

Other conditions are so cheap we’ll probably always check them absent a good reason not to, even in production. Example 1(a)’s min <= max is at this other end of the scale: It’s so dirt cheap to check that it’s unlikely we’ll ever have a performance reason to disable it. [2]

So it makes perfect sense that if Examples 1(a) and 1(b) appear in the same source file, the developer will want to enable checking for 1(b)’s assertion only by some kind of manual override to explicitly request it, and enable checking for 1(a)’s assertion all the time.

3. Give an example of an asserted condition that is in general impossible to evaluate, and so cannot be checked.

One common example is is_reachable for pointers or other iterators, to say that if we increment an iterator enough times we can make it equal to (refer to the same object as) a second iterator:

// Example 3: Very reasonable, but generally not checkable

auto first_iterator = /*...*/;
auto last_iterator  = /*...*/;
MyAssert( is_reachable(first_iterator, last_iterator) );
std::find( first_iterator, last_iterator, value );

In general, there’s no way to write is_reachable. You could try to increment first_iterator repeatedly until it becomes equal to last_iterator, but when the latter is not reachable that might never happen and even just trying would often be undefined behavior.

You might be tempted to test is_reachable using std::distance:

MyAssert( std::distance(first_iterator, last_iterator) >= 0 );

… but that would be horribly wrong. Can you see why?

Take a moment to think about it before continuing…

… okay. The answer is that std::distance itself requires that last_iterator is reachable from first_iterator, otherwise it’s undefined behavior. So this maybe-tempting-looking alternative actually assumes what we want to prove, and so it’s not useful for this purpose. (GotW #100 will consider in detail the general question of preconditions of contract subexpressions, which covers examples like this one.)

Can these kinds of conditions still be useful?

Yes. In practice, these kinds of conditions spell out “this is a formal comment.” Static analyzers and other tools may be able to test such a condition in a subset of cases; for example, at some call sites an analyzer may be able to infer statically that two iterators point into different containers and so one isn’t reachable from the other. Alternatively, the tools might support special pseudofunction names that they recognize when you use them in assertion expressions to give information to the tool. So the conditions can still be useful, even if they can’t generally be checked the normal way, by just evaluating them and inspecting the result.

4. How do these questions help answer:

a) what “levels” of asserted conditions we should be able to express?

There’s a wide spectrum of “expensiveness” of assertion conditions, ranging from cheap to arbitrarily high to even impossible. In the post-C++20 contracts proposal at [3], this is partly captured by the proposed basic levels of default, audit, and axiom, roughly intended to represent “cheap,” “expensive,” and “impossible” respectively.

Because we need to check these with different frequencies (or not at all), we need a way to enable and disable checking for subsets of assertions independently, even when they’re in the same piece of code.

GUIDELINE: Distinguish between (at least) “cheap,” “expensive,” and “impossible” to evaluate assertions. If you develop your own assertion system for in-house use, support enabling/disabling at least these kinds of assertions independently. [1] I say “at least” because what’s “expensive” is subjective and will vary from program to program, from team to team… and even within a program from your code to your third-party library’s code that you’re calling. Having just two preset “cheap” and “expensive” levels is minimal, but useful.

b) why the assertions we can “practically” write are a subset of all the ones we might “ideally” like to write?

It can be useful to distinguish between all ideal assertions, meaning everything that has to be true at various points in the program for it to run correctly, and the practical assertions, meaning the subset of those that can be reasonably expressed as a C++ expression and checked. In GotW #97 question 3, part of the solution says that “if an assertion fails” then…

there is a program bug, possibly in the assertion itself. The first place to look for the bug is in this same function, because if prior contracts were well tested then likely this function created the first unexpected state.

If we could write all ideal assertions, and exercise all control flow and data flow during testing, then a failed assertion would definitely mean a bug in the same function where it was written. Because we realistically can’t write and exercise them all, though, we could be observing a secondary effect from a bug that happened earlier. Still, this function is the first place to start looking for the bug.

Notes

[1] Upcoming GotWs will cover preconditions and violation handling. For handlers, we’ll cover additional distinctions such as categories of violations (e.g., to distinguish safety-related checks vs. other checks).

[2] As always, any checks left on in production would often install a different handler, such as a log-and-continue handler rather than a terminating handler; see GotW #97 Question 4, and note [1].

[3] G. Dos Reis, J. D. Garcia, J. Lakos, A. Meredith, N. Myers, and B. Stroustrup. “P0542: Support for contract based programming in C++” (WG21 paper, June 2018).

Acknowledgments

Thank you to the following for their feedback on this material: Joshua Berne, Guy Davidson, J. Daniel Garcia, Gábor Horváth, Maciej J., Andrzej Krzemieński.

GotW #98: Assertion levels (Difficulty: 5/10)

This special Guru of the Week series focuses on contracts. We covered basic assertions in GotW #97… but not all asserted conditions are created equal.

JG Questions

Given some assertion syntax:

SomeAssert( condition );  // expresses that ‘condition’ must be true

1. Give one example each of an asserted condition whose run-time evaluation is:

a) super cheap

b) arbitrarily expensive

Guru Questions

2. What does the answer to Question 1 imply for assertion checking? Explain.

3. Give an example of an asserted condition that is in general impossible to evaluate, and so cannot be checked. Can these kinds of conditions still be useful?

4. How do these questions help answer:

a) what “levels” of asserted conditions we should be able to express?

b) why the assertions we can “practically” write are a subset of all the ones we might “ideally” like to write?

GotW #97 Solution: Assertions (Difficulty: 4/10)

Assertions have been a foundational tool for writing understandable computer code since we could write computer code… far older than C’s assert() macro, they go back to at least John von Neumann and Herman Goldstine (1947) and Alan Turing (1949). [1,2] How well do we understand them… exactly?

1. What is an assertion, and what is it used for?

An assertion documents the expected state of specific program variables at the point where the assertion is written, in a testable way so that we can find program bugs — logic errors that have led to corrupted program state. An assertion is always about finding bugs, because something the programmer thought would always be true was found to actually be false (oops).

For example, this line states that the program does not expect min to exceed max, and if it does the code has a bug somewhere:

// Example 1: A sample assertion

assert( min <= max );

If in this example min did exceed max, that would mean we have found a bug and we need to go fix this code.

GUIDELINE: Assert liberally. [3] The more sure you are that an assertion can’t be false, the more valuable it is if it is ever found to be false. And in addition to finding bugs today, assertions verify that what you believe is “obviously true” and wrote correctly today actually stays true as the code is maintained in the future.

GUIDELINE: Asserted conditions should never have side effects on normal execution. Assertions are only about finding bugs, not doing program work. And asserted conditions only evaluated if they’re enabled, so any side effects won’t happen when they’re not enabled; they might sometimes perform local side effects, such as to do logging or allocate memory, but the program should never rely on them happening or not happening. For example, adding an assertion to your code should never make a logically “pure” function into an impure function. (Note that “no side effects on normal execution” is always automatically true for violation handlers even when an assertion system such as proposed in [4] allows arbitrary custom violation handlers to be installed, because those are executed only if we discover that we’re in a corrupted state and so are already outside of normal execution. [5] For conditions, it’s up to us to make sure it’s true.)

2. C++20 supports two main assertion facilities… For each one, briefly summarize how it works, when it is evaluated, and whether it is possible for the programmer to specify a message to be displayed if the assertion fails.

assert

The C-style assert is a macro that is evaluated at execution time (hopefully enabled at least during your unit testing! see question 4) if NDEBUG is not set. The condition we pass it must be a compilable boolean expression, something that can be evaluated and converted to bool.

It doesn’t directly support a separate message string, but implementations will print the failed condition itself, and so a common technique is to embed the information in the condition itself in a way that doesn’t affect the result. For example, a common idiom is to append &&"message"  (a fancy way of saying &&true):

// Example 2(a): A sample assert() with a message

assert( min <= max
        && "BUG: argh, miscalculated min and max again" );

static_assert

The C++11 static_assert is evaluated at compile time, and so the condition has to be a “boolean constant expression” that only refers to compile-time known values. For example:

// Example 2(b): A sample static_assert() with a message

static_assert( sizeof(int) >= 4,
               "UNSUPPORTED PLATFORM: int must be at least 4 bytes" );

It has always supported a message string, and C++17 made the message optional.

Bonus: [[assert: ?

Looking forward, a proposed post-C++20 syntax for assertions would support it as a language feature, which has a number advantages including that it’s not a macro. [4] This version would be evaluated at execution time if checking is enabled. Currently that proposal does not have an explicit provision for a message and so programmers would use the && "message" idiom to add a message. For example:

// Example 2(c): An assertion along the lines proposed in [4]

[[assert( min <= max
          && "BUG: argh, miscalculated min and max again" )]] ;

3. If an assertion fails, what does that indicate, and who is responsible for fixing the failure?

A failed assertion means that we checked and found the tested variables to be in an unexpected state, which means at least that part of the program’s state is corrupt. Because the program should never have been able to reach that state, two things are true:

  • There is a program bug, possibly in the assertion itself. The first place to look for the bug is in this same function, because if prior contracts were well tested then likely this function created the first unexpected state. [5]
  • The program cannot recover programmatically by reporting a run-time error to the calling code (via an exception, error code, or similar), because by definition the program is in a state it was not designed to handle, so the calling code isn’t ready for that state. It’s time to terminate and restart the program. (There are advanced techniques that involve dumping and restarting an isolated portion of possibly tainted state, but that’s a system-level recovery strategy for an impossible-to-handle fault, not a handling strategy for run-time error.) Instead, the bug should be reported to the human developer who can fix the bug.

GUIDELINE: Don’t use assertions to report run-time errors. Run-time errors should be reported using exceptions, error codes, or similar. For example, don’t use an assertion to check that a remote host is available, or that the user types valid input. Yes, std::logic_error was originally created to report bugs (logic errors) using an exception, but this is now widely understood to be a mistake; don’t follow that pattern.

Referring to this example:

// Example 3

void f() {
    int min = /* some computation */;
    int max = /* some other computation */;

    // still yawn more yawn computation

    assert( min <= max );         // A

    // ...
}

In this code, if the assertion at line A is false, that means what the function actually did before the assertion doesn’t match what the assertion condition expected, so there is a bug somewhere in this function — either before or within the assertion.

This demonstrates why assertions are primarily about eliminating bugs, which is why we test…

4. Are assertions primarily about checking at compile time, at test time, or at run time? Explain.

Assertions are primarily about finding bugs at test time. But assertions can also be useful at other times because of some well-known adages: “the sooner the better,” “better late than never,” and “never [will] I ever.”

Bonus points for pointing out that there is also a fourth time in the development cycle I didn’t list in the question, when assertions can be profitably checked. Here they are:

Of course this can be even more nuanced. For example, you might make different decisions about enabling assertions if your “run time” is an end user’s machine, or a server farm, or a honeypot. Also, checking isn’t free and so you may enable run-time checking for severe classes of bugs but not others, such as that an operating system component may require checking in production for all out-of-bounds violations and other potential security bugs, but not non-security classes of bugs.

First, “the sooner the better”: It’s always legal and useful to find bugs as early as possible. If we can find a bug even before actually executing a compiled test, then that’s wonderful. This is a form of shift-left. We love shift-left. There are two of these times in the graphic:

  • (Earliest, best) Edit time: By using a static analysis tool that is aware of assert and can detect some violations statically, you can get some diagnostics as you’re writing your code, even before you try to compile it! Note that to recognize the assert macro, you want to run the static analyzer in debug mode; analyzers that run after macro substitution won’t see an assert condition when the code is set to make release builds since the macro will expand to nothing. Also, usually this kind of diagnostic uses heuristics and works on a best-effort basis that catches some mistakes while not diagnosing others that look similar. But it does shift some diagnostics pretty much all the way left to the point where you’re actually writing the code, which is great when it works… and you still always have the next three assertion checking times available as a safety net.
  • (Early) Compile time: If a bug that depends only on compile-time information can be detected at compile time even before actually executing a compiled test, then that’s wonderful. This is one reason static_assert exists: so that we can express tests that are guaranteed to be performed at compile time.

Next, the primary target:

  • Test time: This is the main time tests are executed. It can be during developer-machine unit testing, regression testing, build-lab integration testing, or any other flavor of testing. The point is to find bugs before they escape into production, and inform the programmer so they can fix their bug.

Finally, “better late than never” (safety net) or “never [will] I ever” (intolerable severe condition):

  • (Late) Run time: Even after we release our code, it can be useful to have a way to enable checking at run time to at least log-and-continue (e.g., using facilities such as [6] or [7]). One motivation is to know if a bug made it through testing and out into the field and get better late-debug diagnostics; this is sometimes called shift-right but I think of it as much as being about belt-and-suspenders. Another motivation is to ensure that severe classes of bugs ensure execution will halt outright if we cannot tolerate continuing after such a fault is detected.

Importantly, in all cases the motivation is still debugging: Findings bugs early is still debugging, just better (sooner and less expensive). And finding bugs late that escaped into production is still debugging, just worse (later and more expensive). Each of these times is a successive safety net for bugs that make it past the earlier times.

Because at run time we may want to log a failed assertion, our assertion violation handler should be able to USE-A logging system, but the relationship really is USES-A. An assertion violation handling system IS-NOT-A general-purpose logging system, and so a contracts language feature shouldn’t be designed around such a goal. [5]

Finally, speaking of run time: Note that it can be useful to write an assertion, and also write code that does some handling if the assertion is false. Here’s an example from [8]:

// Example 4: Defense in depth

int DoSomething(int x) {

    assert( x != 0 && "x should be nonzero" ); // finds bug, if checked
    if( x == 0 ) {
        return INVALID_COOKIE; // robustness fallback, if not checked
    }

    // do useful work

}

You might see this pattern written interleaved as follows to avoid duplicating the condition, and this is one of the major patterns that leads to writing assert(!"message"):

    if( x == 0 ) {
        assert( !"x should be nonzero" ); // finds bug, if checked
        return INVALID_COOKIE; // robustness fallback, if not checked
    }

At first this may look like it’s conflating the distinct “bug” and “error” categories we saw in Question 3’s table. But that’s not the case at all, it’s actually deliberately using both categories to implement “defense in depth”: We assert something in testing to minimize actual occurrences, but then in production still provide fallback handling for robustness in case a bug does slip through, for example if our test datasets didn’t exercise the bug but in production we hit some live data that does.

Notes

With thanks to Wikipedia for the first two references.

[1] H. H. Goldstine and J. von Neumann. “Planning and Coding of problems for an Electronic Computing Instrument” (Report on the Mathematical and Logical Aspects of an Electronic Computing Instrument, Part II, Volume I, p. 12; Institute for Advanced Study, April 1947).

[2] Alan Turing. “Checking a Large Routine” (Report of a Conference on High Speed Automatic Calculating Machines, pp. 67-9, June 1949).

[3] H. Sutter and A. Alexandrescu. C++ Coding Standards (Addison-Wesley, 2004). Item 68, “Assert liberally to document internal assumptions and invariants.”

[4] G. Dos Reis, J. D. Garcia, J. Lakos, A. Meredith, N. Myers, and B. Stroustrup. “P0542: Support for contract based programming in C++” (WG21 paper, June 2018). To keep it as legal compilable (if unenforced) C++20 for this article I modified the syntax from : to ( ). That’s not a statement of preference, it’s just so the examples can compile today to make them easier to check.

[5] Upcoming GotWs will cover postconditions, preconditions, invariants, and violation handling.

[6] G. Melman. spdlog: Fast C++ logging library (GitHub).

[7] Event Tracing for Windows (ETW) (Microsoft, 2018).

[8] H. Sutter. “P2064: Assumptions” (WG21 paper, 2020).

Acknowledgments

Thank you to the following for their comments on drafts of this article: Joshua Berne, Gábor Horváth, Andrzej Krzemieński, Andrew Sutton. Thanks also to Reddit user “evaned” and Anton Dyachenko for additional feedback.

GotW #97: Assertions (Difficulty: 4/10)

Assertions have been a foundational tool for writing understandable computer code since we could write computer code… far older than C’s assert() macro, they go back to at least John von Neumann and Herman Goldstine (1947) and Alan Turing (1949). [1,2] How well do we understand them… exactly?

[Update: On second thought, I’ll break the “assertions” and “postconditions” into two GotWs. This GotW has the assertion questions, slightly reordered for flow, and GotW #99 will cover postconditions.]

JG Questions

1. What is an assertion, and what is it used for?

2. C++20 supports two main assertion facilities:

  • assert
  • static_assert

For each one, briefly summarize how it works, when it is evaluated, and whether it is possible for the programmer to specify a message to be displayed if the assertion fails.

Guru Questions

3. If an assertion fails, what does that indicate, and who is responsible for fixing the failure? Refer to the following example assertion code in your answer.

void f() {
    int min = /* some computation */;
    int max = /* some other computation */;

    // still yawn more yawn computation

    assert (min <= max);         // A

    // ...
}

4. Are assertions primarily about checking at compile time, at test time, or at run time? Explain.

Notes

Thanks to Wikipedia for pointing out these references.

[1] H. H. Goldstine and J. von Neumann. “Planning and Coding of problems for an Electronic Computing Instrument” (Report on the Mathematical and Logical Aspects of an Electronic Computing Instrument, Part II, Volume I, p. 12; Institute for Advanced Study, April 1947.)

[2] Alan Turing. “Checking a Large Routine” (Report of a Conference on High Speed Automatic Calculating Machines, pp. 67-9, June 1949).

Firsts in 2020 (or, A little dose of good news)

2020 has been mostly terrible. That includes for the C++ committee and many of our communities, where just this month we lost Beman Dawes. Beman was one of the most important and influential C++ experts in the world, and made his many contributions mostly behind the scenes. I and everyone else who has ever benefited from any of the standardized STL, Boost, C++Now, std::filesystem, C++98/11/14/17, and more — so, really, most people who have ever used C++ — all owe Beman a debt of gratitude. We miss him greatly.

To end the year with a little dose of good news, I thought I’d mention a just few positive C++ accomplishments that did happen for 2020, and were happier “first-ever” achievements.

First, the big one…

C++20 is the first ever “D&E-complete” release of C++. In February, we completed C++20, which is the first release of Standard C++ that includes every feature that Bjarne Stroustrup envisioned for C++’s evolution in his 1994 book The Design and Evolution of C++ (aka D&E), including concepts, coroutines, modules, and more, except only for one minor feature (unified function call syntax). Thank you to Bjarne for sticking with it until we got there, and personally doing the heavy lifting to drive important features like concepts into Standard C++!

C++20 is the first release of C++ that added a feature that made the standard smaller. When I talk about the importance of simplifying C++ by judiciously adding features that let programmers express their intent directly, some people legitimately object that adding a feature makes C++ bigger and more complex. I reply “but it makes C++ code simpler” and “if it replaces something more complex then we can teach a simpler C++ for new code,” but those effects have been hard to measure concretely. Now in C++20 for the first time we added a new feature that made the standard smaller: We added the C++20 spaceship operator to the language, but we also applied it throughout the C++ standard library and that made the library specification nearly 20 pages shorter — a net reduction. So for the first time we can measure that, yes, adding a feature to C++ can make C++ smaller. Thank you to everyone who helped me with that proposal and who are listed in the Acknowledgements in the link, and especially to Walter E. Brown, Jens Maurer, Barry Revzin, and David Stone!

First year for all-virtual standards meetings, including EWG and LEWG. Since March, for the first time all major subgroups including the two main design subgroups of EWG (language) and LEWG (library) have been having virtual meetings by telecon or Zoom and making progress in between face-to-face meetings. We’ve also had a record number of nearly 20 virtual subgroup meetings on average per month. It’s great to see that, despite the pandemic, the committee has continued work on C++23 and other long-pole features, and in November we were able to formally adopt the first C++23 features into our brand-new C++23 working draft. Thank you once again to JF Bastien (EWG), Bryce Lelbach (LEWG), and their assistants, and all the other subgroup chairs and participants for patiently supporting these changes that we had to invent and transition to at short notice, and as we continue to work out the kinks as we go!

Many first virtual conferences. And of course 2020 saw many of our C++ conferences hold their first virtual events (and create new ones like Pure Virtual C++), in the face of huge uncertainties and technical challenges with bleeding-edge technologies, to make it all work far more smoothly than we really would have had any right to expect on such short notice. Thank you to the organizers for working so busily behind the scenes to make it possible to have a facsimile of our face-to-face conferences until we can meet again in person!

Here’s hoping that by this time next year we will all be doing better in every way, and have a happier 2021 to reflect upon. Thank you again, everyone, for your interest in C++ and support for our many C++ events, forums, and other communities large and small, and best wishes for a great 2021.