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The main objective of any product manager is to ensure the process of product management runs smoothly and flawlessly: from the concept to release. However, it's all about the ideal world.

In order to present a brilliant product to the world, it is important to learn how to use convenient and multifunctional online tools that facilitate management and open up new opportunities for managers, expanding their professional horizons. In this article, you will find 15 smart tools that contribute to the professional success of product managers in 2019.

PVS-Studio supports analyzing projects developed in C, C++, C#, and Java. You can use the analyzer under Windows, Linux, and macOS. This small article will tell you the basics of analyzing C and C++ code in Linux environment.

Installation

There are different ways to install PVS-Studio under Linux, depending on your distro type. The most convenient and preferred method is to use the repository, since it allows auto-updating the analyzer upon releasing new versions. Another option is to use the installation package, which you can get here.

And our homeland's pushing us For reaching knowledge higher heights.

The available and interesting literature on science is a magic wand that helps the progress not to slow down and move forward. Thanks to interesting science literature, children begin to study voluntarily and with interest, while adults expand their horizons and do not allow the brain to relax. Biology, astronomy and mathematics supplant the saga about the elves and intergalactic ships. But while Western countries' nonfiction was always in smooth progress from Jules Verne to Eliezer S. Yudkowsky, then opposite it experienced both ups and downs in Russia.

This week we issue a really huge selection of all the essential news you might have missed on Front-end development. Make sure to check the latest updates on CSS, HTML, and JavaScript.

User interfaces of modern enterprise applications are quite complex. You, as a developer, often need to implement in-app navigation, validate user input, show or hide screens based on user preferences. For better UX, your app should be capable of saving state to the disk when the app is suspending and of restoring state when the app is resuming.

ReactiveUI provides facilities allowing you to persist application state by serializing the view model tree when the app is shutting down or suspending. Suspension events vary per platform. ReactiveUI uses the Exit event for WPF, ActivityPaused for Xamarin.Android, DidEnterBackground for Xamarin.iOS, OnLaunched for UWP.

In this tutorial we are going to build a sample application which demonstrates the use of the ReactiveUI Suspension feature with Avalonia — a cross-platform .NET Core XAML-based GUI framework. You are expected to be familiar with the MVVM pattern and with reactive extensions before reading this note. Steps described in the tutorial should work if you are using Windows 10 or Ubuntu 18 and have .NET Core SDK installed. Let's get started! Source code of the app described in this tutorial is available on GitHub.

Let's say, your website offers content, products, or services for people from different regions or countries who speak different languages. Search engines will probably count this as duplicate content, leading to low rankings.

Over the years, the PVS-Studio team has been developing the same-name static analyzer. At this point the analyzer represents a complex software solution, which provides the analysis of such programming languages, as C, C++, C# and Java on Windows, Linux and macOS platforms. Just recently the Java language joined the ranks of supported languages. The PVS-Studio analyzer has proved itself as a reliable tool among C++ and C# developers in quite some time, whereas for Java audience PVS-Studio is still a newcomer. Many haven't even heard of the analyzer, and those who had, aren't quite familiar with all its abilities. So in this article, I'd like to introduce PVS-Studio Java to you, talk about the ways to start it and its abilities.

Nowadays, talking to conversational agents is becoming a daily routine, and it is crucial for dialogue systems to generate responses as human-like as possible. As one of the main aspects, primary attention should be given to providing emotionally aware responses to users. In this article, we are going to describe the recurrent neural network architecture for emotion detection in textual conversations, that participated in SemEval-2019 Task 3 “EmoContext”, that is, an annual workshop on semantic evaluation. The task objective is to classify emotion (i.e. happy, sad, angry, and others) in a 3-turn conversational data set.

When mulling over the best programming language to use for data science, Python and R ring a bell (very quickly). While there are a lot of languages like C, C++, Java, Julia, Perl, and Scala, it's protected to state that Python and R are the harbingers in data science.

While a great deal of data researchers will discuss the customary shortcomings like data wrangling in R or data representation in Python, ongoing improvements like Altair for Python or R have adequately reacted to these shortcomings.

So which one would it be a good idea for you to decide for your next data investigation venture?

R has been ruling this space for a long time now. This bodes well as this programming language was explicitly intended for analysts.

Nowadays there is no need to implement the physics of objects from scratch for game development because there are a lot of libraries for this purpose. Bullet was actively used in many AAA games, virtual reality projects, various simulations and machine learning. And it is still used, being, for example, one of the Red Dead Redemption and Red Dead Redemption 2 engines. So why not check the Bullet with PVS-Studio to see what errors static analysis can detect in such a large-scale physics simulation project.

In my previous article I described how to achieve the "Maybe" monad behavior using async/await operators. This time I am going to show how to implement another popular design pattern "Reader Monad" using the same techniques.

That pattern allows implicit passing some context into some function without using function parameters or shared global objects and it can be considered as yet another way to implement dependency injection. For example:

class Config { public string Template; }

public static async Task Main()
{
    Console.WriteLine(await GreetGuys().Apply(new Config {Template = "Hi, {0}!"}));
    //(Hi, John!, Hi, Jose!)

    Console.WriteLine(await GreetGuys().Apply(new Config {Template = "¡Hola, {0}!" }));
    //(¡Hola, John!, ¡Hola, Jose!)
}

//These functions do not have any link to any instance of the Config class.
public static async Reader<(string gJohn, string gJose)> GreetGuys() 
    => (await Greet("John"), await Greet("Jose"));

static async Reader<string> Greet(string name) 
    => string.Format(await ExtractTemplate(), name);

static async Reader<string> ExtractTemplate() 
    => await Reader<string>.Read<Config>(c => c.Template);

Our attention was recently attracted by the Electronic Arts repository on GitHub. It's tiny, and of the twenty-three projects available there, only a few C++ libraries seemed interesting: EASTL, EAStdC, EABase, EAThread, EATest, EAMain, and EAAssert. The projects themselves are tiny too (about 10 files each), so bugs were found only in the «largest» project of 20 files :D But we did find them, and they do look interesting! As I was writing this post, we were also having a lively discussion of EA games and the company's policy :D

Numerous typos and Copy-Paste code became the main topic of the additional article about checking the Haiku code by the PVS-Studio analyzer. Yet this article mostly tells about errors related to thoughtlessness and failed refactoring, rather than to typos. The errors found demonstrate how strong the human factor is in software development.

The story of how the PVS-Studio static analyzer and the Haiku OS code met goes back to the year 2015. It was an exciting experiment and useful experience for teams of both projects. Why the experiment? At that moment, we didn't have the analyzer for Linux and we wouldn't have it for another year and a half. Anyway, efforts of enthusiasts from our team have been rewarded: we got acquainted with Haiku developers and increased the code quality, widened our error base with rare bugs made by developers and refined the analyzer. Now you can check the Haiku code for errors easily and quickly.

Young product managers aim to rapidly learn the fundamentals of their role and master the craft. However, there are no magic power, specific book or a class that can give you 100% of professional mastery.

You want it all, you want it now. But it will surely take some time to make you a product management guru. This post contains a set of relevant resources about product management for those who prefer to read, listen and watch.

In order to verify the quality of software, you have to use a lot of different tools, including static and dynamic analyzers. In this article, we'll try to figure out why only one type of analysis, whether static or dynamic, may not be enough for comprehensive software analysis and why it's preferable to use both.

In this article, I'm going to tell you about PVS-Studio, an analyzer for C and C++ code, and show you how to use it in the Visual C++ environment. This guide is specifically intended for beginner users.

PVS-Studio is a tool for detecting software bugs and potential vulnerabilities in the source code of software written in C, C++, C#, and Java. The analyzer runs on Windows, Linux, and macOS.

Preface

What is ageing? We can define ageing as a process of accumulation of the damage which is just a side-effect of normal metabolism. While researchers still poorly understand how metabolic processes cause damage accumulation, and how accumulated damage causes pathology, the damage itself – the structural difference between old tissue and young tissue – is categorized and understood pretty well. By repairing damage and restoring the previous undamaged – young – state of an organism, we can really rejuvenate it! It sounds very promising, and so it is. And for some types of damage (for example, for senescent cells) it is already proved to work!

Today in our virtual studio, somewhere between cold, rainy Saint-Petersburg and warm, sunny Mountain View, we meet Aubrey de Grey, again! For those of you who are not familiar with him, here is a brief introduction.

Last time, we used SFINAE to detect whether a type had a definition, and we used that in combination with if constexpr and generic lambdas so that code could use the type if it is defined, while still being accepted by the compiler (and being discarded) if the type is not defined.

However, our usage had a few issues, some minor annoyance, some more frustrating.

• You had to say struct all the time.
• If the type didn’t exist, the act of naming it caused the type to be injected into the current namespace, not the namespace you expected the type to be in.
• You must use the struct technique with an unqualified name. You can’t use it to probe a type that you didn’t import into the current namespace.

We can fix all three of the problems with a single solution: Predeclare the type in the desired namespace.