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Manual resource management in low level C-style C++ code might be annoying. It's not practical to create good enough RAII wrappers for every single C API you use, but approaches with goto cleanup or loads of nested if (success) hurt readability.

A defer macro to the rescue! The deferred lambda will be executed on scope exit, no matter how it happens: you can return from any point, throw an exception (if allowed), or even use a goto to an outer scope. It is truly zero-cost and doesn't rely on C runtime or standard library, so it can be used even in kernel development.

This article is based on the experience of developing the memsafe library, which, using the Clang plugin, adds safe memory management and invalidation control of reference data types to C++ during source code compilation.

Let’s say you’ve created your own USTRUCT in C++ and now you want to serialize it.

Usually, it’s enough to simply mark the desired fields with SaveGame. But here’s the problem — in order for this to work, the fields themselves must support serialization.
Unfortunately, one of our variables doesn’t.

In my case, it’s a struct called FNonSerializableStruct. Because of that, only the second struct gets serialized, even though we marked both with SaveGame.

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.

I needed to create a category panel for placeable items in the UI — like the ones you see in city-building games. As a legacy, I inherited a ready-made UENUM, which may be modified in the future.

Naturally, I didn’t want to manually create and tweak every single widget — especially knowing that the list of categories might change later. I wanted something simple and reusable: just run a For each loop, generate everything on the fly, and ideally make it work for any enum, not just this one.

And there was a way! When you define a UENUM, Unreal automatically generates all the metadata and creates a corresponding UEnum object, which is a UObject. All you have to do is use that data properly.

The most common types of software bugs are memory management bugs. And very often they lead to the most tragic consequences. There are many types of memory bugs, but the only ones that matter now are memory leaks due to circular references, when two or more objects directly or indirectly refer to each other, causing the RAM available to the application to gradually decrease because it cannot be freed.

Memory leaks due to circular references are the most difficult to analyze, while all other types have been successfully solved for a long time. All other memory bugs can be solved at the programming language level (for example, with garbage collectors, borrow checking or library templates), but the problem of memory leaks due to circular references remains unsolved to this day.

But it seems to me that there is a very simple way to solve the problem of memory leaks due to circular references in a program, which can be implemented in almost any typed programming language, of course, if you do not use the all-permissive keyword unsafe for Rust or std::reinterpret_cast in the case of C++.

There have been many discussions about which programming language is better in terms of security and correctness of source code (by "correctness and security" we mean the absence of various errors in the program that manifest themselves at the stage of its execution and lead to the issuance of an incorrect result or unexpected behavior). And some programming languages, such as SPARK or OCaml, were even specially developed to facilitate the proof of program correctness.

Is it possible to write programs without errors at all?

According to the description,

Tree-sitter is a parser generator tool and an incremental parsing library. It can build a concrete syntax tree for a source file and efficiently update the syntax tree as the source file is edited.

But how does Tree-sitter handle languages that require a preprocessing stage?

Hi Everyone!

In this article we a little bit will analyze of code of Windows XP and will compile the calculator application using GCC x64 in Windows 10 environment. We will look what kind of errors I faced during the build and the methods how to solve them. At the end we will launch the build of the calc.exe application.

Have a nice reading!

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?

Practically all programming languages are built either on the principle of similarity (to make like this one, only with its own blackjack) or to realize some new concept (modularity, purity of functional calculations, etc.). Or both at the same time.

But in any case, the creator of a new programming language doesn't take his ideas randomly out of thin air. They are still based on his previous experience, obsession with the new concept and other initial settings and constraints.

Is there a minimal set of lexemes, operators, or syntactic constructs that can be used to construct an arbitrary grammar for a modern general-purpose programming language?

Network programming in C++ can be challenging. But even a greater challenge is to find educational content that will arm you with the knowledge on how to apply your networking skills in real applications.

In this article you can learn the basics of socket communication and many ways how you can design your internal messaging protocols.

Asynchronous programming is commonly employed for efficient implementation of network interactions in C++. The essence of this approach lies in the fact that the results of socket read/write functions are not immediately available but become accessible after some time. This approach allows for loading the processor with useful work during the wait for data. Various implementations of this approach exist, such as callbacks, actors, future/promise, coroutines. In C++, these implementations are available as libraries from third-party developers or can be implemented independently.

Coroutines are the most challenging to implement as they require writing platform-dependent code. However, the recent version of the C++ 20 language standard introduces support for coroutines at the compiler and standard library levels. Coroutines are functions that can suspend their execution, preserving their state, and later return to that state to resume the function's work. The compiler automatically creates a checkpoint with the coroutine's state.

For a comprehensive understanding of C++ 20 coroutines, refer to this article. Below, we examine a code example using coroutines and describe important points applied during implementation.

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)

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:

Hash, salt, SHA-1, SHA-2, std::hash.. To a non-programming person that may come up as some kind of a recipe that just does not seem to add up. In a sense, this is indeed supposed to be a gibberish to any third party and a strong, helpful mechanism for us, programmers. 

At the start of writing this article, I had one clear idea to get across the table: to finally unveil this mystery of hashing in C++ for beginners. I, a beginner myself, also wanted to solidify my knowledge in this area; so let’s get started.

How do people usually write a server if they don't really care about performance? A program starts, then starts accepting incoming connections from clients and starts a new thread for each client, which is engaged in servicing this client. If you use framework, like Spring or Flask or Poco there, then it does something like this inside itself - the only difference is the threads can be reused, that is, taken from a certain pool. It's all quite convenient, but not too effective (and Spring is bad). Most likely, your threads serving clients do not live long and most of the time they are waiting either to receive data from the client or to send it to the client - that is, they are waiting for some system calls to return. Creating an OS thread is quite an expensive operation, as is context switching between OS threads. If you want to be able to serve a lot of customers efficiently, you need to come up with something else. For example, callbacks, but they are pretty inconvenient (though there are different opinions on this).

Another option is to use non-blocking I/O in combination with some kind of implementation of user-space threads (fibers). In this article I will show you how to write all this with your own hands.

The point of this article is to explore Lambda functions, their dirrerences from regular functions and how they are implemented, based on C++, Python and Java programming languages.

Throughout this article I will be using godbolt.org to compile code and see machine code or byte code.

I just started to learn Game Development, and decided to run write my personal blog about it. So there you can find information(resources, blogs, courses, books) that i've gathered and my personal problems with learning)

Author: Denis Zherdetskiy