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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.

In any project, a great deal of importance is placed on the selection of server hardware and WebRTC streaming is no exception. One of the key principles of such a selection is balance – the hardware should be powerful enough to handle the streams with no drops in quality, but not too powerful so as to waste resources. So, how does one choose the right server?

People increasingly start optimizing the process of finding code errors using static analyzers. Nowadays, we can choose from a variety of products to view analysis results. This post covers the ways how to view an analyzer report in the most stylish and feature-rich IDE among multifunctional ones – VSCode. The SARIF format and a special plugin for it allow us to perform our task. Keep reading to find out about this. Let's get going!

Once I was asked to save a traffic dump of an Instagram app while viewing one particular user profile. Simply saving the traffic dump on the router didn't make sense because the app used TLS to communicate with the server. Existing solutions didn't work because they worked with an older version of Instagram.

Below I will describe how I managed to do it myself using mitmproxy, ghidra and frida.

With the help of the ESLint and Prettier features, you can automate the formatting of your code, make it more expressive and accurate, correspond to specific rules, and avoid errors and bottlenecks even before uploading the code to the shared source storage...

OpenAPI specification

One of the nicest features of Go is the power of code generation. go generate command serves as a Swish knife allowing you to generate enums, mocks and stubs. In this article, we will employ this feature to generate a Go code from OpenAPI specification. OpenAPI specification is a modern industrial standard for REST API. This standard has fantastic tooling support and allows you to conveniently render and validate the spec. We are going to befriend the power of Go code generation with the elegance and clarity of the OpenAPI specification. In this way, you don't have to manually update the Go boilerplate code after every change in the spec. You also ensure that your docs and your code are a single entity, as your code is being begotten from the docs.

Let's start dead-simple: we have a service that accepts order requests. Let's declare endpoint order/10045234 that accepts PUT requests, where 10045234 is an ID of a particular order. We expect to receive an order as a JSON payload in the following format.

    {"item":  "Tea Table Green", "price":  106}

How can describe this endpoint in the OpenAPI spec?

The PVS-Studio analyzer already has plugins for such IDEs from JetBrains as Rider, IntelliJ IDEA and Android Studio. Somehow we missed another IDE - CLion. The time has come to make amends! But why would you need PVS-Studio if CLion already has the code analyzer? What problems appeared during development? Keep reading to find answers to these questions.

Static code analysis allows you to identify and eliminate many defects at an early stage. Moreover, it's possible to detect dormant errors that don't show themselves when they appear. They can cause many problems in the future and it requires many hours of debugging to detect them. Let's look at an example of such a dormant error.

Monitoring systems are a vital tool for any system administrator, because they can be used to extract specific information from services, such that:

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?

In the comment sections of our articles about our server there are often users who say: "Why would you jump through so many hoops, when you can do the same with a single line of code in FFmpeg!?"

In the first part of You don't know Redis, I built an app using Redis as a primary database. For most people, it might sound unusual simply because the key-value data structure seems suboptimal for handling complex data models.

In practice, the choice of a database often depends on the application’s data-access patterns as well as the current and possible future requirements.

Redis was a perfect database for a Q&A board. I described how I took advantage of sorted sets and hashes data types to build features efficiently with less code.

Now I need to extend the Q&A board with registration/login functionality.

I will use Redis again. There are two reasons for that.

Firstly, I want to avoid the extra complexity that comes with adding yet another database.

Secondly, based on the requirements that I have, Redis is suitable for the task.

Important to note, that user registration and login is not always about only email and password handling. Users may have a lot of relations with other data which can grow complex over time.

Despite Redis being suitable for my task, it may not be a good choice for other projects.

Always define what data structure you need now and may need in the future to pick the right database.

RAM disk, this is a disk based on RAM memory chips. This kind of disk is not able to retain data after the power is turned off (unless a supporting battery is used), but has an exceptionally high read/write speed (especially for random access) and an unlimited lifespan. It is important in tasks that need a lot of cycles to write over information, even professional SSD drives don’t live long. To the operating system the RAM disk is indistinguishable from an SSD or HDD disk and no special drivers or setup is required. Unlike a disk that is virtually located in the computer’s RAM memory, where the maximum memory capacity is limited to 128-256 GB in the best consumer motherboards, a RAM disk for a PCIe slot, in general, has no volume limits and can work in any MB with a PCIe slot.

Java 8 introduced two kinds of functional expressions: lambda expressions like s -> System.out.println(s) and method references like System.out::println. At first, developers were more enthusiastic about method references: they are often more compact, you don't need to think up the parameter name, and, as urban legends say, method references are somewhat more optimal than lambda expressions. Over time, however, the enthusiasm waned. One of the problems with method references is the difficulty in debugging.

This article is aimed to describe FreeBSD OS as a platform to launch cloud guest OSes with simple API capabilities, using MyBee and DevOPS I really like!

We, the PVS-Studio static code analyzer developers, have a peculiar view on beauty. On the beauty of bugs. We like to find grace in errors, examine them, try to guess how they appeared. Today we have an interesting case when the concepts of length and size got mixed up in the code.

Google Colorizing Transformer vs Deoldify