C++ *

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.

One of our readers recommended paying heed to the Espressif IoT Development Framework. He found an error in the project code and asked if the PVS-Studio static analyzer could find it. The analyzer can't detect this specific error so far, but it managed to spot many others. Based on this story and the errors found, we decided to write a classic article about checking an open source project. Enjoy exploring what IoT devices can do to shoot you in the foot.

This part covers the use of typemaps, complex & weird cases, and debugging suggestions. This part requires an understanding of Part 1 - usage of SWIG in simple cases.

This is a practical Android-first guide, with Android Studio project you can play with.

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.

For some people, the introduction of a static analyzer into a project seems like an insurmountable obstacle. It is widely believed that the amount of analysis results issued after the first run is so large that only two options seem reasonable: do not mess with it at all or refocus all people on fixing warnings. In this article, we will try to dispel this myth by implementing and configuring the analyzer on a GTK project.

Repository

concurrencpp allows applications to write asynchronous code easily and safely by using executors and coroutines.

By using concurrencpp applications can break down big procedures that need to be processed asynchronously into smaller tasks that run concurrently and work in a co-operative manner to achieve the wanted result.

concurrencpp also allows applications to write parallel algorithms more easily by using parallel coroutines.

concurrencpp main advantages are:

• Being able to write non-blocking, asynchronous code easily by using the C++20 coroutines and the co_await keyword.
• Being able to write modern concurrent code without having to rely on low-level concurrency primitives like locks and condition variables.
• The concurrency runtime manages all low-level resources such as threads automatically.
• Reducing the possibility of race conditions, data races and deadlocks by using high-level objects with built-in synchronization.
• concurrencpp provides various types of commonly used executors with a complete coroutine integration.
• Applications can extend the library by using their own provided executors.
• Applications automatically scale-up to use all hardware processors (cores).

Introduction

rotor is a non-intrusive event loop friendly C++ actor micro framework, similar to its elder brothers like caf and sobjectizer. The new release came out under the flag of pluginization, which affects the entire lifetime of an actor.