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Passing parameters to a function

When passing parameter to a function, category of a passed expression is implicitly converted to the category of function parameter: void f(TO_TYPE p); FROM_TYPE x; f(x); This implicit conversion takes place the same way as during an assignment (see "Assignment" section above) except that function definition cannot contain "auto" types.

I always pay attention to assessing the complexity of programming in a particular language. Programming is indeed not an easy task and this is perceived as a fact and usually does not require any confirmation.

But the concept of “complexity” is akin to the term “heap”. For some, five coconuts is not so much, but for someone who ate one and “didn’t want any more,” this means that even one coconut will be too much for him.

The same goes for the complexity of programs. It seems that the constant increase in the complexity of programs is obvious to everyone and is observed in all areas of application of IT technologies, and programming languages themselves become more and more complex as they develop, but assessing “complexity” using numerical metrics is a problem. obviously a thankless task, but also “You can’t manage what you can’t measure...”

Typically, talk of “complexity” only implies value judgments without any numerical evaluation. And since I am personally interested in the issue of the complexity of programming languages, I decided to calculate the complexity of implementing the gcc compiler on some conditional “parrots”. What if we could see some patterns of difficulty changing over time?

I wrote a small e-book about terrible tips for C++ developers. Actually, it describes bad programming practices and explains why it's better to avoid them. However, every chapter of this mini-book starts with a terrible tip — just for fun.

By the way, these tips may seem artificial but believe me, they are based on the real experience. In other words, the described terrible tips occur in developers' lives — that's why it's worth discussing them. First of all, this book will be useful for junior developers. But more skilled C++ developers can also find interesting and useful tips.

Even though it's a mini-book, it clearly does not fit into the Habr format. Too many words. So, I decided to write here the review. Here is the link to find the full version of the mini-book: 60 terrible tips for a C++ developer.

If you still hesitate whether to read it or not, below you will find a list of terrible tips that will be discussed in the mini-book.

View the terrible tips:

Sometimes programming with mutexes gets too complicated and messy. Maybe you need to meet a new friend — the Event Loop pattern.

Flipper Zero is an open-source multi-tool for geeks and penetration testers. It so happened that the Flipper Zero project and the PVS-Studio analyzer crossed paths. A philosophical question: should we check the project, if the project developers have already started fixing errors? Let's try to do this.

General

Before discussing the topic I’d like to start with a general suggestion not to use multiple inheritance and especially diamond unless you are strongly forced to. You may use e.g. composition or aggregation instead.

Well, “Diamond inheritance problem” is some kind of steady expression which formed many years ago. You can easily find a lot of articles suggesting usage of “virtual public” to avoid the ambiguity and so on. For instance, https://en.wikipedia.org/wiki/Multiple_inheritance

 That is not wrong as for the problem stated but anyway it is quite one-side statement.
 Below you can find:

• difference in memory allocation and initialization order between public and public virtual inheritance (examples 1, 2),
• examples of practical usage of both public and public virtual inheritance (examples 3, 4).

If you’ve been working with Unreal Engine for a while, you’ve probably come across nodes that let you call a function now and get the result later — while also continuing execution once the function completes.

There are two articles on Russian, the author of which writes a virtual machine (interpreter) for executing a simple bytecode and then applies different optimizations to make this virtual machine faster. Besides that, there is a compiler of a simple C-like language into this bytecode. After reading this article and getting familiar with the compiler, I thought that it would be interesting to try writing a virtual machine for this language that would be able to apply JIT-compilation to this bytecode with the libjit library. This article describes the experience of doing that.

I found several articles online that describe the usage of this library, but those that I saw, describe the compilation of concrete programs with libjit, while I was interested in compiling arbitrary bytecode. For people interested in further reading, there is an official titorial, a series of articles and a series of comparisons (in Russian).

The implementation was done in C++ because we aren`t playing games here. All my code is in my repository. The "main" branch has just the interpreter of the PigletVM bytecode; "labels-with-fallbacks" has a partial JIT compilation implementation (that doesn`t support JUMP instructions), "full-jit" has fully working JIT-compilationl; "making-jit-code-faster" makes code generated by JIT work faster and "universal-base-vm*" branches merge the interpreter and JIT-compilation implementations, by implementing a base generalised executor, which can be used for different implementations of PigletVM (both the interpreter and libjit compilation)

An example of using Electron + React JS and a native ffmpeg addon to access a webcamera

This guide may be helpful to someone who is trying to find a way
to work with Electron if they need to use a c++ library or code

I was looking for a more realistic example than a simple 'hello world' and i didn't succeed

Here are the links in advance:

- electron - https://github.com/khomin/electron_camera_ffmpeg

- addon - https://github.com/khomin/electron_ffmpeg_addon_camera

So let me share my experience...

It's freezing outside, everyone has already decorated the Christmas tree and bought tangerines. New Year is coming! So, it's time to meet the Top 10 interesting bugs found by the PVS-Studio C++ analyzer in 2021.

This article investigates why the standard library needs a way to deduce a common type, how it is implemented and how it works.

It's cool when enthusiastic developers create a working clone of a famous game. It's even cooler when people are ready to continue the development of such projects! In this article, we check TheXTech with PVS-Studio. TheXTech is an open implementation of the game from the Super Mario universe.

Couple of weeks ago (or to be more precise, on July 2, 2021), the legendary BitTorrent protocol turned twenty years old. Created by Bram Cohen, the protocol has been developing rapidly since its inception, and has quickly become one of the most popular ways to exchange files. So why not check out a couple of long-lived related projects with the PVS-Studio analyzer for Linux?

PVS-Studio is a static analysis tool that helps find errors in software source code. This time PVS-Studio looked for bugs in Storm Engine's source code.

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!

SWIG is a tool for generating cross-language interfaces - it provides interoperability of C++ and other languages (C++ and Java in our case). SWIG just simplifies and automizes cross-language interaction; otherwise, you may end up with thousands of lines of handwritten JNI code - but SWIG covers this for you.

This guide is for newbies (Part 1) and for those who experienced in SWIG (part 2). I'm starting from basic setup and usage and ending with complex & weird cases encountered in development. The latter cases are not so complex, rather usual for modern languages, which SWIG doesn't support yet (as lambdas).

This guide is practical. In opposition to overcomplicated huge-volume SWIG documentation, this guide is showing the cases practically. The bits developed by myself while working on the different projects or taken from StackOverflow. This guide allows you to quick-start an Android Studio project and giving practical examples of using SWIG. The link to the Android Studio project is here.

This guide is Android-first. The goal was to make it simple to onboard for Android developers. There are many articles about SWIG, but they are mainly for desktop Java applications, and it is quite an overhead to just try them on Android to check if the solution for the particular problem is working. While this guide includes an Android Studio project, with which you can play around instantly. Of course, all the information given here applies to any Java application.

Warning! I should warn you, that nowadays cross-platform development offers powerful tools. If you are developing a new application it is much more cost-efficient in practice to use ReactNative, Flutter of Kotlin-Native than the SWIG. While SWIG is more suitable to connect the C++ library or existing C++ application core.