Lightning Talk: How Far Should You Indent Your Code? - The Number Of The Counting

by Dave Steffen

Coding Standards have to say something about how we indent our code.  Is there a definitive answer?

C++20 Concepts for Nicer Compiler Errors

by Daniel Lemire

In C++, templates enable generic programming by allowing functions and classes to operate on different data types without sacrificing type safety. Defined using the template keyword, they let developers write reusable, type-agnostic code, such as functions (e.g., template <typename T> max(T a, T b)) or classes (e.g., std::vector), where the type T is specified at compile time.

Historically, the C++ language has tended to produce complicated compiler error messages. The main culprit is template metaprogramming. C++ templates are powerful but complex. When errors occur in template code, the compiler generates long, verbose messages with nested type information, often involving deep template instantiations. A simple mistake in a template function can produce a message spanning multiple lines with obscure type names.

Let us consider an example. In C++, we often use the ‘Standard Template Library (STL)’. It includes a useful dynamic array template: std::vector. A vector manages a sequence of elements with automatic memory handling and flexible sizing. Unlike fixed-size arrays, it can grow or shrink at runtime through operations like push_back to append elements or pop_back to remove them. You can store just about anything in an std::vector but there are some limits. For example, your type must be copyable.

Announcing the 3rd Keynote for Meeting C++ 2025: its Anthony Williams!

by Jens Weller

Today I have the honor to announce that Anthony Williams completes the keynotes for Meeting C++ 2025!

Anthony Williams is well known for his book "C++ Concurrency in Action", has been an active in the committee through the BSI since 2001. He is well known for his work on concurrency and one of the architects and implementers of std::thread and other concurrency features in C++. He gave an An introduction to multithreading in C++20 at Meeting C++ 2022 in the online track. I am looking forward to welcome Anthony in person in Berlin this year!

Guide to Linear Algebra With the Eigen C++ Library

by Daniel Hanson

Linear algebra is an essential part of scientific programming, particularly in domains such as quantitative finance, data science, physics, and medical research.  It is also relevant to imaging in game development.  As C++ did not have all the convenient built-in multidimensional array capabilities and supporting libraries that came with typical Fortran platforms, scientific programmers making the transition to C++ back in the late 1990’s and early 2000's often found themselves in an inconvenient situation with limited options.  These included building up this functionality mostly from scratch, wrestling with interfaces to numerical Fortran libraries such as BLAS and LAPACK, or somehow convincing management to invest in a third-party commercial C++ linear algebra library.

The situation has improved substantially over the years with the development of several well-regarded open-source linear algebra libraries for C++.  One in particular that has become popular, first released in 2006, is the Eigen library.  It has been adopted for use within both the TensorFlow machine learning library and the Stan Math Library, as well as at CERN, and it can also be found in the implementation of high-performance quantitative trading strategies in C++.

In this talk, we will examine the setup and basics of the Eigen library, followed by a discussion of some of its more advanced features, including applications of matrix decompositions frequently used in quantitative work, as well as its compatibility with STL algorithms.  It will conclude with an overview of how it can be used within the context of the C++26 BLAS interface proposal (P1673), via an interface with std::mdspan now available in C++23.

Using C++ Type Aliasing to Avoid the ODR Problem with Conditional Compilation, Part 1

by Raymond Chen

Some time ago, I discussed the C++ concept of ill-formed no diagnostic required (IFNDR). A common accidental source of this is violating the One Definition Rule (ODR) by defining a class or function differently based on compile-time switches.

// widget.h

struct Widget
{
    Widget();

    void SetName(std::string const& name);

    ⟦ more stuff ⟧

#ifdef EXTRA_WIDGET_DEBUGGING
    Logger m_logger;

    void Log(std::string const& message) {
        m_logger.log(message);
    }
#else
    void Log(std::string const& message) {
        // no extra logging
    }
#endif

    std::string m_name;
};

If one .cpp file is compiled with extra widget debugging enabled, but another is compiled with extra widget debugging disabled, and they are linked together, then you have a One Definition Rule violation because the Widget structure and the Widget::Log method have conflicting definitions.

But all is not lost.

Lightning Talk: Amortized O(1) Complexity in C++

by Andreas Weis

We will take a quick look at how amortized analysis for algorithms works. We will use two examples from the standard library to demonstrate this and show how in one place, the standard's interpretation of amortized constant complexity is at odds with the usual use of the term.

Lightning Talk: Using PMR in C++ Embedded Systems for Functional Safety

by Scott Dixon

Dynamic memory is often disallowed in high-assurance, c++ embedded systems but, when examining the reasons why, C++17 Polymorphic Memory Resources emerge as an unexpected solution to enable the use of C++ standard library constructs for such projects. My talk will explore how PMR can be used to meet functional safety requirements and to build embedded systems that are robust, performant, and testable.

C++26: More constexpr in the Standard Library

by Sandor Dargo

P2562R1: constexpr stable sorting

This paper proposes making std::stable_sort, std::stable_partition, std::inplace_merge, and their ranges counterparts usable in constant expressions. While many algorithms have become constexpr over the years, this family related to stable sorting had remained exceptions — until now.

The recent introduction of constexpr containers gives extra motivation for this proposal. If you can construct a container at compile time, it’s only natural to want to sort it there, too. More importantly, a constexpr std::vector can now support efficient, stable sorting algorithms.

A key question is whether the algorithm can meet its computational complexity requirements under the constraints of constant evaluation. Fortunately, std::is_constant_evaluated() provides an escape hatch for implementations. For deeper details, check out the proposal itself.

Back to Basics: Unit Testing in C++

by Dave Steffen

Unit Testing is a big, complicated subject. With good advice coming in from books, conference talks, and blog posts beyond count, it's a daunting topic even for experienced developers.  Can we make the subject more approachable?

Yes we can.  If we look a little deeper, there are some fundamental principles behind the advice. Further, these principles seem to belong to a small number of "domains", each addressing a very different aspect of unit testing and software development.

For example, "Test error conditions separately", "Tests should be easy to read", and "Write the unit tests first" are all great advice, but each is aiming for a very different goal.

In this talk, we'll survey these domains of unit testing practice, identify some of the basic practices involved in each, and put the larger discussion of unit testing into a more useful context.  We will also see how some unit testing practices enhance or conflict with others, and how these controversies reveal deep philosophical questions that have real consequences for how we go about the day-to-day activity of testing our code.

The voting on the talks for Meeting C++ 2025 has begun!

by Jens Weller

Once again its time for the C++ community to take a look at the submitted talks for Meeting C++ 2025! Thanks to all folks who have submitted a talk to this years conference! Your contribution will create another great conference in Berlin and online! And special thanks to all folks who have bought tickets already for the conference, you'll have a bit more weight in the voting to shape this years program!

With your voting session you can contribute to the talk selection for this years conference. In total 107 talks are submitted by 73 speakers. With this year the call for talks closes earlier than in the past, when for a few years it had extended to match the submission date with CppCon. Since last year CppCon has moved its deadline into early/mid May, which is a bit too early. For the future I plan to have the call for talks close around the beginning of June. A period of 2 months to submit should be enough, also this allows for an earlier release of the program. This than gives speakers more time to get their talks ready and Meeting C++ more time to advertise the program...