Java *

In this article, I want to describe my experience of paying off technical debt on our project in the form of a guide. In this guide, I will highlight some of the most common cases of technical debt and suggest methods for solving them. Since this is a rather extensive topic, I will recommend several books for study, because I do not see it possible to talk about everything within the framework of this article. Everything described applies to the BackEnd part, but it may be suitable for other developers. I would be glad if you share your experience on this topic in the comments.

This is a series of articles dedicated to the optimal choice between different systems on a real project or an architectural interview.

This topic seemed relevant to me because such tasks can be encountered both at work and at an interview for System Design Interview and you will have to choose between these two types of DBMS. I plunged into this issue and will tell you what and how. What is better in each case, what are the advantages and disadvantages of these systems and which one to choose, I will show with several examples at the end of the article.

SQL or NoSQL?

At first glance making REST and Apache Kafka compatible seems quite a challenge. However Innotech team nailed the task. Kirill Voronkin, Lead Developer at Innotech, shared the details on transforming unsynchronized queries into synchronized.

In previous post I've described an example of kogito-based microservice on quarkus in native mode, containing one embedded pmml model with decision tree. While it can be successfully used for prototyping purposes, in the real life microservice might contain several prediction models. From the first view I've got an impression, that inclusion of several models should be a trivial extension of the prototype with one model. We were completely wrong in our assumption, that's the reason, why I've decided to write this post. Another reason, is absence of guides, in which 2 (or more models) are put inside DMN diagrams in kogito framework.

Very often we've heard that some frameworks fit together so good, that they are considered as "match made in heaven". In this article I would like to share our experience regarding integration of those frameworks.

In this article I have described problems I have faced during integration Apache Camel with Spring Boot Actuator Prometheus for collecting metrics and my solution to solve this problem (which I haven't found over the internet).

For the first time PVS-Studio provided support for the CWE classification in the 6.21 release. It took place on January 15, 2018. Years have passed since then and we would like to tell you about the improvements related to the support of this classification in the latest analyzer version.

It seems that the problem of calculating the absolute value of a number is completely trivial. If the number is negative, change the sign. Otherwise, just leave it as it is. In Java, it may look something like this:

public static double abs(double value) {
  if (value < 0) {
    return -value;
  }
  return value;
}

It seems to be too easy even for a junior interview question. Are there any pitfalls here?

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.

The previous year has been very distressing for businesses and employees. Though, software development didn’t get so much affected and is still thriving. While tech expansion is continuing, Java development is also going under significant transformation.

The arrival of new concepts and technologies has imposed a question mark on the potential of Java developers. From wearable applications to AI solutions, Java usage is a matter of concern for peers.

Moreover, it is high time that developers enhance their skills as to the changing demands of the industry. If you are a Java developer, surely you too would be wondering what I am talking about what things you should learn.

In microservice world the problem of high load is exteremely big especially when we have a REST API which is accessed quite extensively. Why do we need throttling? The main answer is to decrease the load of the service at the moment.

Different frameworks have different solutions, mostly some additional libraries. Also there is a Guava RateLimiter and Bucket4J . What is interesting Spring MVC being one of the most popular solutions for building REST APIs (thank you Spring Boot) doesn't have any built in rate limiter. As for external solutions there not that many ways around.

Today, I would like to present a tiny experimental library specific for Spring MVC. It is called SpringRateLimitter. The library is very tiny ,works in runtime. The idea is to annotate entire rest controller or specific method , than count the number of incoming requests for the annotated URI and based on the values check if we exceed the allowed number of calls. In case of exceeding an HTTP error code 429 is thrown and after the throttling period is over , the endpoint is available again.

So How does it look like. As first step Maven dependency must be added

What happens to your MongoDB replica set when it comes to failures like network partitioning, restarting, reconfiguration of the existing topology, etc.? This question is especially important these days because of the popularity gained by the multi-cloud model where chances of these scenarios are quite realistic.

However, is there a solution, preferably a free one, for testing such cases that would obviate the need of writing manual scripts and poring over the official documentation? As software developers, we would be better off preparing our applications in advance to survive these failures.

This article is about security. I’ll focus on this in the context of web applications, but I’ll also touch on other types of applications. Before I describe approaches and frameworks, I want to tell you a story.

Background

Throughout my years working in the IT sphere, I’ve had the opportunity to work on projects in a variety of fields. Even though the process of authenticating requirements remained relatively consistent, methods of implementing the authorization mechanism tended to be quite different from project to project. Authorization had to be written practically from scratch for the specific goals of each project; we had to develop an architectural solution, then modify it with changing requirements, test it, etc. All this was considered a common process that developers could not avoid. Every time someone implemented a new architectural approach, we felt more and more that we should come up with a general approach that would cover the main authorization tasks and (most importantly) could be reused on other applications. This article takes a look at a generalized architectural approach to authorization based on an example of a developed framework.

Approaches to Creating a Framework

As usual, before developing something new, we need to decide what problems we’re trying to solve, how the framework will help us solve them, and whether or not there is already a solution to these issues. I’ll walk you through each step, starting with identifying issues and describing our desired solution.

We’re focusing on two styles of coding: imperative and declarative. Imperative style is about how to get a result; declarative is about what you want to get as a result.

If you feel like the New Year just came, and you missed the first half of January, then all this time you've been busy looking for tricky bugs in the code you maintain. It also means that our article is what you need. PVS-Studio has checked the ELKI open source project to show you errors that may occur in the code, how cunningly they can hide there, and how you can deal with them.

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.

Privet, comrads!

In this article i’ll show how easy it is to setup Spring Java app with Kafka message brocker. We will use docker containers for kafka zookeeper/brocker apps and configure plaintext authorization for access from both local and external net.

Link to final project on github can be picked up at the end of the article.

In this digital world, people prefer to work remotely. There are numerous tasks that each of us goes through every day. If I talk about an application's usage, then it has been predicted that there will be a 25% increase in global app downloads between 2018 and 2022. 

But it can be quite challenging for organizations to maintain and create multiple passwords. Hence, a password management software can be a great choice to manage this effectively. It is like your bank locker, where one can store numerous passwords. The users only need a master password to access the software.

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