Compilers *

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.

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?

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)

This is a translation of my own article

The release of NewLang language with a brand new "feature" is coming, a remodeled version of the preprocessor that allows you to extend the language syntax to create different DSL dialects using macros.

What is it about?

DSL (Subject Oriented Language) is a programming language specialized for a specific application area. It is believed that the use of DSL significantly increases the level of abstractness of the code, and this allows to develop more quickly and efficiently and greatly simplifies the solution of many problems.

Conditionally, we can distinguish two approaches to DSL implementation:

• Development of independent syntax translators using lexer and parser generators to define the grammar of the target language through BNF (Backus–Naur form) and regular expressions (Lex, Yacc, ANTLR, etc.) and then compiling the resulting grammar into machine code.
• Development or integration of the DSL dialect into a general-purpose language (metalanguage), including the use of various libraries or special parsers / preprocessors.

We will talk about the second option, namely the implementation of DSL on the basis of general-purpose languages (metalanguages) and the new implementation of macros in NewLang as the basis for DSL development.

Nfun is an embedded language and expression executor that supports primitive types, arrays, structures and lambda expressions.

Most likely, you have already met tasks that require such a tool, and in this article I want to show examples of its application, its capabilities and why it may be useful to you.

print(1 + 2)

Structured logging is gaining more and more popularity in the developers' community. In this article I'd like to demonstrate how we can use structured logging with the Microsoft.Extensions.Logging package and show the idea how we can extend it using the new features of C# 10.

Commercial static analyzers perform deeper and fuller code analysis compared to compilers. Let's see what PVS-Studio found in the source code of the LLVM 13.0.0 project.

November 10, 2020 was in many ways a landmark event in the microprocessor industry: Apple unveiled its new Mac Mini, the main feature of which was the new M1 chip, developed in-house. It is not an exaggeration to say that this processor is a landmark achievement for the ARM ecosystem: finally an ARM architecture chip whose performance surpassed x86 architecture chips from competitors such as Intel, a niche that had been dominated for decades.

But the main interest for us is not the M1 processor itself, but the Rosetta 2 binary translation technology. This allows the user to run legacy x86 software that has not been migrated to the ARM architecture. Apple has a lot of experience in developing binary translation solutions and is a recognized leader in this area. The first version of the Rosetta binary translator appeared in 2006 were it aided Apple in the transition from PowerPC to x86 architecture. Although this time platforms were different from those of 2006, it was obvious that all the experience that Apple engineers had accumulated over the years, was not lost, but used to develop the next version - Rosetta 2.

We were keen to compare this new solution from Apple, a similar product Huawei ExaGear (with its lineage from Eltechs ExaGear) developed by our team. At the same time, we evaluated the performance of binary translation from x86 to Arm provided by Microsoft (part of MS Windows 10 for Arm devices) on the Huawei MateBook E laptop. At present, these are the only other x86 to Arm binary translation solution that we are aware of on the open market.

PHP is widely known as an interpreted programming language used mainly for website development. However, few people know that PHP also has a compiler to .NET – PeachPie. But how well is it made? Will the static analyzer be able to find actual bugs in this compiler? Let's find out!

Recently PVS-Studio has implemented a major feature—we supported intermodular analysis of C++ projects. This article covers our and other tools' implementations. You'll also find out how to try this feature and what we managed to detect using it.

__int128 add1(__int128 a, __int128 b) {
    return b + a;
}

Introduction

I don’t care what your dragon’s said, it’s a lie. Dragons lie. You don’t know what’s waiting for you on the other side.

Michael Swanwick, The Iron Dragon’s Daughter