This is a continuation of a small note series about regular checks of the Blender project with the PVS-Studio static analyzer. The aim of these publications is to demonstrate how it is beneficial to use static code analysis tools regularly. In doing so, many errors can be found at the earliest stage, and fixing them will be cheap and fast.

Recently, we have been monitoring changes in the Blender project, or rather, what errors appear in the new code. This compels us to write notes and discuss interesting topics. Here is one question I’d like to cover.

C# capabilities keep expanding from year to year. New features enrich software development. However, their advantages may not always be so obvious. For example, the good old yield. To some developers, especially beginners, it's like magic - inexplicable, but intriguing. This article shows how yield works and what this peculiar word hides. Have fun reading!

PVS-Studio is a static analyzer that allows to find many problems hidden in the source code. Among them there are also errors related to application security. For example, the analyzer has recently learned to identify the presence of confidential data such as passwords in the code. The OWASP Top Ten list includes this potential vulnerability. It is much more dangerous than it may seem at first glance. What makes it so dangerous? How can a static analyzer save us from it? That's what you'll know about (and more) in this article!

Surely every C# developer has used out-parameters. It seems that everything is extremely simple and clear with them. But is it really so? For a kickoff, let's start with a self-test task.

Let's say you use GitHub, write code, and do other fun stuff. You also use a static analyzer to enhance your work quality and optimize the timing. Once you come up with an idea - why not view the errors that the analyzer gave right in GitHub? Yeah, and also it would be great if it looked nice. So, what should you do? The answer is very simple. SARIF is right for you. This article will cover what SARIF is and how to set it up. Enjoy the reading!

There is an open project COVID-19 CovidSim Model, written in C++. There is also a PVS-Studio static code analyzer that detects errors very well. One day they met. Embrace the fragility of mathematical modeling algorithms and why you need to make every effort to enhance the code quality.

In PVS-Studio, we often check various compilers' code and post the results in our blog. Decompiler programs, however, seem to be a bit neglected. To restore justice in this world, we analyzed the ILSpy decompiler's source code. Let's take a look at the peculiar things PVS-Studio found.

You may have already read a recent article about the first PVS-Studio run and filtration of warnings. We used the GTK 4 project as an example. It's about time we worked with the received report in more detail. Our regular readers may have already guessed that this article will be a description of errors found in the code.

The PVS-Studio analyzer is regularly updated with new diagnostic rules. Curiously enough, diagnostics often detect suspicious code fragments before the end of the work. For example, such a situation may happen while testing on open-source projects. So, let's take a look at one of these interesting finding.

If you feel like the New Year just came, and you missed the first half of January, then all this time you've been busy looking for tricky bugs in the code you maintain. It also means that our article is what you need. PVS-Studio has checked the ELKI open source project to show you errors that may occur in the code, how cunningly they can hide there, and how you can deal with them.