CppCon 2026

Move semantics and perfect forwarding, introduced in C++11, are quite impactful features that still remain a source of confusion even for some experienced developers. This talk builds understanding from the ground up: what problem move semantics solves, how rvalue references enable it, and why the rules work the way they do.

We start with the cost of unnecessary copies and how move constructors and move assignment operators let us transfer resources instead of duplicating them. We then look at how std::move doesn't actually move anything — and what it really does. From there we tackle the forwarding problem: why writing a single function that preserves the value category of its arguments is necessary, how forwarding references (also known as "universal reference" in the past) solve it, and what std::forward does under the hood.

Along the way we cover the practical details that trip people up: reference collapsing rules, the interaction between overload resolution and reference binding, when the compiler generates move operations and when it doesn't, and the cases where std::move can actually pessimize your code. We also discuss trade-offs in parameter passing — by value, by const reference, or by forwarding reference — so attendees should have a clearer model for making these decisions in their own code.

At the end we will look into std::forward_like and explore how it is different from std::forward .

No prior knowledge of rvalue references is assumed. Familiarity with copy constructors, destructors, and basic templates is helpful.

C++ templates are one of the language’s most powerful yet often misunderstood features. This talk walks the audience through the entire template landscape, starting with the basic syntax and definition, moving through function and class templates, and culminating in advanced techniques.

Attendees will learn how template argument deduction works, why implicit requirements matter, and how function overloading can replace error-prone macro tricks. Real-world examples, including a flexible register abstraction used in production code, show how generic programming can deliver type-safe, high-performance solutions without sacrificing readability and performance (zero cost abstraction).

By the end of the session, participants will feel confident writing their own generic components, understand the trade-offs of different template features, and have a toolbox of best-practice patterns they can apply immediately to their projects.

Memory leaks are very hard to treat. We have reliable tools like valgrind or AddressSanitizer to tell us whether or not an application has leaked memory, but current tools cannot tell us where the leak happens (they can tell us where the allocation happened,which is not the same).

I show that it is possible to run an analysis that is equivalent to running a garbage detection pass after every instruction and use that to find the actual cause of memory leaks in open source applications.

Using a garbage detection algorithm on record-and-replay recording, one can overcome the most obvious obstacle: stopping a program a program after every instruction or running garbage detection algorithms is very slow, but we can effectively run a bisection search on the recorded timeline to avoid having to evaluate after every instruction.

The goal is attribution to source code. Are we limited to reporting the instruction that overwrites the last reference to allocated memory or can we actually diagnose a specific error for a concrete function?

Tooling Track sessions are sponsored by Optiver.

Scripting in a C++ game engine should not cost you the engine's native performance. This talk shows how C++26 static reflection and std::meta::substitute in particular can lift a scripting language's bytecode into C++ template structures that the compiler optimizes away entirely, collapsing the interpreter dispatch loop into the same machine code you'd write by hand. Scripting languages like AngelScript and Lua are invaluable in C++ engines: they give designers a fast iteration loop without rebuilding the engine. But they come with a paradox. The engine you chose for raw performance now spends cycles on every frame interpreting a slower language, juggling a software stack and checking types at runtime. We will walk through the technique step by step, starting from a plain bytecode interpreter and ending at a fully reflected program where a scripted sum(0..10) compiles to mov eax, 45; ret. Along the way you'll learn the core C++26 reflection primitives (^^, [: :], std::meta::substitute), how to assemble bytecode into structural templates like block<> and loop<>, and how these techniques generalize to embedding any stack or register based scripting language in your engine with zero runtime overhead.