Lukas Barth

I often encounter variations of the following problem: You are given two or more lists (as e.g. std::vector) of elements and you want to sort them “in parallel”, using one of the lists as keys. I always found the solutions to these kind of problems to be clunky - but with C++23 (or the excellent range-v3 library) we get a very elegant way of doing this.

If you build an application that uses large, contiguous amounts of memory, it can increase your performance if you allocate this memory in so-called huge pages. Linux offers you two ways of doing that - a legacy way and a modern way. This article describes the modern way of using huge pages, so called transparent huge pages (THP) and applies the techniques from a previous article to verify that we actually got huge pages. pages.

In fact, CodeChecker is much more than just a front-end to Clang’s Static Analyzer (clangsa from here on…) - but using it just to drive clangsa is already awesome enough that I think you should use it to hunt for bugs in your C++ projects.

In this article, I’ll show how to set up and use CodeChecker for a quick one-off analysis of a CMake based C++ project, and outline how to use CodeChecker in a collaborative setting with the option of integrating it into a CI system. If you are not on C++, CodeChecker might still be for you, as it also supports multiple analyzers for e.g. Java, Python, Go, or JavaScript.

This blog now uses Carl Schwan’s great idea (and code) to add a comment section to this (static) website. The whole thing works by using a Mastodon/Fediverse post as an “anchor” for a comment thread.