“Due to complex environments and distributed engineering teams, enterprise customers struggle to efficiently and securely deploy and manage IDEs, AI tools, and remote environments all at once. These struggles naturally slow businesses down and result in missed opportunities,” said Brian Noll, VP of sales and global partnership at JetBrains Americas.

JetBrains IDE Services provides a central management hub for five different JetBrains products: IDE Provisioner, AI Enterprise, License Vault, Code With Me Enterprise, and CodeCanvas.

IDE Provisioner provides IDE updates as needed to ensure outdated versions are not used, AI Enterprise provides AI-driven productivity features, License Vault automates the distribution of JetBrains IDE licenses, Code With Me Enterprise provides pair programming, and CodeCanvas handles the configuration of the development environment.

“With the release of JetBrains IDE Services, we are giving customers a centralized way to manage their development stack at the organizational level and dramatically improve the productivity of entire engineering departments with the inclusion of enterprise versions of JetBrains AI, Code With Me, and CodeCanvas in the suite,” said Noll.

The service is available with an on-premises deployment option, but the company has plans to add a cloud offering as well.

Through the new platform, development teams will be able to automate processes related to the integration of application changes. Additionally, they will be able to test apps as well as make updates to users’ devices.

TeamCity is a platform created by JetBrains but designed for large enterprises. TeamCity Pipelines, on the other hand, is built entirely for small or medium-sized businesses.

“I’m happy to announce that we’re launching a streamlined solution to address the specific needs of those smaller engineering teams today,” said Marco Behler, product manager of TeamCity Pipelines.

The company’s solution is to simplify the user interface, as well as incorporate AI into the platform. JetBrains believes this will help provide intelligent configuration suggestions.

“TeamCity Pipelines is straightforward to use and configure while also being efficient and resource-saving”, added Marco Bahler.

TeamCity Pipelines has YAML files. They serve to store, modify files and more.

The company states its intention to integrate the solution provided by TeamCity Pipelines into the JetBrains IDE. This will make it easier for developers to build, run, and debug, while not requiring developers to shut down their IDEs.

JetBrains has officially launched the stable release of Kotlin Multiplatform. This innovative technology empowers developers to efficiently share code across an array of platforms, including iOS, Android, desktop, web, server-side, and many others. Kotlin Multiplatform has already gained traction among elite development teams at major corporations, such as Netflix, VMware, Cash App, McDonald’s, Electrolux, and Phillips. This groundbreaking release is poised to revolutionize the way we approach cross-platform development.

The framework offers a fully stabilized API, streamlined project configuration, enhanced interoperability with Objective-C and Swift, along with notable improvements in build times and
overall performance.

“Where other technologies abstract away or completely replace platform-specific app development, Kotlin Multiplatform is complementary to existing platform-specific technologies and is geared toward replacing platform-agnostic business logic. It’s a new tool in the toolbox as opposed to replacing the toolbox,” said David Henry and Mel Yahya, Developers at Netflix.

The foremost advantage of Kotlin Multiplatform lies in its flexibility. Developers have the liberty to selectively share a portion of their application’s logic, allowing them to craft native code when the need arises to interface with platform-specific APIs or construct native user interfaces. What’s even more enticing is the synergy achieved by combining Kotlin Multiplatform with Compose Multiplatform, a declarative framework designed for seamless UI sharing across diverse platforms.

“Now that Kotlin Multiplatform is stable, developers can feel much more confident about adopting it for their production projects, as JetBrains will be evolving Kotlin Multiplatform according to the strictest backward compatibility rules. Now is a great time to start using Kotlin Multiplatform for sharing code and to explore Compose Multiplatform’s capabilities for sharing UIs. We will continue improving the core technology, the libraries, and the tooling to provide the best multiplatform development experience to all,” said Ekaterina Petrova, Product Marketing Manager of Kotlin Multiplatform at JetBrains.

This synergy empowers developers with unparalleled creative freedom, enabling them to share as much as 100% of their codebase, all within the Kotlin ecosystem. While Compose Multiplatform stands as a stable solution for Android and desktop, it is being explored experimentally for web applications and is currently in its Alpha stage for iOS.

In addition to Kotlin’s enhanced cross-platform tools, future updates will improve the iOS developer experience by providing direct interoperability between Kotlin and Swift and support for SwiftPM.

One of the most remarkable features of Writerside is its AI-based spellchecker and grammar correction tool, which boasts support for over 25 languages. This tool opens up opportunities for creators in various linguistic domains, including English, German, Spanish, and Chinese, to ensure their content is not only technically accurate but also linguistically polished.

Writerside, the innovative authoring and publishing tool by JetBrains, boasts a plethora of remarkable features tailored to enhance the technical documentation creation process. These features include:

• Built-in Git UI: Simplifying version control and collaboration, Writerside incorporates a Git user interface, making it effortless for developers and writers to work together seamlessly.
• Live Preview: Writers can now enjoy a real-time, accurate preview of their documents as they will appear to readers, eliminating the need to wait for a full build to see the final result.
• Markdown and XML Support: Writerside offers versatile support for Markdown, XML, or the combined use of both. Developers can inject semantic attributes and elements to enrich Markdown, and easily convert Markdown elements into XML for a structured and standardized output.
• Ready-to-Use Designs: The tool provides authors with a range of pre-designed templates. Customization options include choosing between dark or light modes, adjusting contrast, selecting soft or vivid skins, and defining accent colors to align with a brand’s identity. This allows content creators to concentrate on their content, without the need to delve into complex layout design or CSS management.
• Automated Testing: Writerside conducts automatic checks for broken links, missing resources, incorrect attribute values, and non-unique IDs. It also features built-in code highlighting and validation, with a comprehensive suite of inspections to ensure document quality and accuracy.
• Single Source of Truth: Writerside maintains a central repository of content for project-wide content reuse, streamlining collaboration and content consistency across a variety of documentation materials.

JetBrains said it uses Writerside internally to write documentation for products ranging from the IntelliJ Platform SDK to the Kotlin programming language.

The Rider 2023 EAP 4 IDE can debug startup code for WebAssembly .NET applications. This is accomplished by changing the order in which the IDE launches the application. Rider waits for the target page to initialize, connects to the debugger, and only then starts loading the application correctly, Infoq wrote on the subject.

Previously, for most WASM projects, the debugger could only connect after the application was initialized, as calculating ports or initializing the connection took some time. The solution added in EAP 4 removes this delay and enables the capture of breakpoints set at the beginning of the application initialization logic.

This new version of Rider is the first to support Astro, an open source tool that can create static HTML sites using popular JavaScript frameworks like React or Vue, while loading fully interactive components when needed. The Astro plugin for Rider can be downloaded from the JetBrains Marketplace or installed directly from the IDE. The plugin includes basic features such as code completion with auto-import, syntax highlighting, refactoring, navigation or proper code formatting. JetBrains plans to add more advanced Astro support in future releases.

The ighlighted feature is related to scaling in and out of the IDE. Developers can increase and decrease the size of UI elements simultaneously.

The community reacted positively to the new release, especially to the information about the Astro plugin. Davor Pihac, senior software engineer, welcomed the Astro plugin support in the Twitter thread for Rider 2023.1 EAP 4.

Today we have chosen to present you with some more detailed information around it, especially for those of you who have the desire to add it to your list of used programming languages.

Java and Kotlin

Kotlin is one of the most popular JVM languages besides Java.

Kotlin is interoperable with Java. If you already know Java, you will probably pick up Kotlin quite easily, as the two languages are quite similar. Developers who know both languages can use Java or Kotlin code in the same project.

Popularity and applications

Although Kotlin is a general-purpose language, it is mostly used for Android app development.

Do you know why this language has gained so much popularity in recent years? Because it was noticed by Google. Back in 2017, Google stated that it would support Kotlin for Android app development over Java.

Many Android apps have been developed using Kotlin, such as Google, Pinterest, Slack, Netflix, N26, Airbnb, and Tinder. Kotlin also works well on other platforms such as iOS, Linux and Windows.

For complete beginner programmers, Hackr.io recommends being able to perform certain tasks before attempting to learn Kotlin.

You should have a basic understanding of computers; the ability to install and manage multiple software products on a computer system, knowledge of Android and iOS for mobile app development, and a basic understanding of back-end and web development.

How to learn Kotlin the easy way?

Like all other programming languages, it’s good to learn Kotlin by practicing and most importantly, having fun. Games are a great way to learn programming and coding, for example.

“While reading the Kotlin documentation is easy and enjoyable, learning everything through examples is another kind of fun.”

write the official Kotlin website.

The language’s website also recommends the TicTacToe game, which is a fun way to test out newly acquired Kotlin skills.

And because AI can be a powerful weapon in the hands of developers if they know how to use it properly, today we’ve chosen to introduce you to some of the best AI tools, according to Marktech Post, that are currently available to developers.

AI Tools That Can Generate Code to Help Programmers

OpenAI Codex

GitHub Copilot, a tool from GitHub to produce code inside common development environments such as Neovim, VS Code, JetBrains, and even in the cloud with GitHub Codespaces, is powered by OpenAI Codex, a model based on GPT-3. It claims it can write code in at least 12 different languages, including BASH, JavaScript, Go, Perl, PHP, Ruby, Swift, and TypeScript. The algorithm is trained on trillions of lines of publicly accessible code from places like GitHub repositories.

Tabnine

Although Tabnine is not an end-to-end code generator, it amps up the integrated development environment’s (IDE) auto-completion capability. Jacob Jackson created Tabnine in Rust when he was a student at the University of Waterloo, and it has now grown into a complete AI-based code completion tool.

CodeT5

Researchers at SalesForce created the open-source programming language paradigm known as CodeT5. The T5 (Text-to-Text Transfer Transformer) framework from Google is its foundation. The researchers used approximately 8.35 million instances of code, together with user comments, from openly available GitHub projects to train CodeT5. The bulk of these datasets was obtained from the CodeSearchNet dataset, containing two C and C# datasets from BigQuery, along with Ruby, JavaScript, Go, Python, PHP, and C and C#.

Polycoder

OpenAI’s Codex has a competition in the form of a Polycoder. The model, created by scientists at Carnegie Mellon University, is based on OpenAI’s GPT-2, which was trained using a 249 GB codebase developed in 12 different programming languages. The creators of PolyCoder claim that the software can write C more precisely than any other model, including Codex. Polycoder is one of the earliest open-source code-generating models, even if most code generators are not.

Cogram

Cogram is a startup from Berlin’s Y-Combinator incubator that creates code for data scientists and Python programmers using Jupyter Notebooks and SQL queries. English-language queries may be written by data scientists and converted by the tool into sophisticated SQL queries with joins and grouping. It works with MySQL, SQLite, PostgreSQL, and Amazon Redshift.

GitHub Copilot

An AI tool called GitHub Copilot may assist you in producing better code. It can create code for you and aid in your comprehension of other people’s code. GPT-3 and OpenAI Codex power Github Copilot.

DeepCode

DeepCode is a code review tool powered by AI that examines your code and makes suggestions for improving it. Code completion, refactoring, and lining are among its many capabilities. For open-source projects, DeepCode is free, while a premium membership is available for private enterprises.

Kite

For Python, Kite is a free AI-powered code completion tool. You will get real-time code completions thanks to machine learning. For a fee, Kite also provides access to premium services, including sophisticated code analysis and refactoring tools. Kite stands out from the competitors since it supports more than 16 languages and 16 code editors. The regular updates to Kite make this machine-learning code aid more dependable and economical than the competition.

TabNine

An AI-powered code completion application called TabNine employs deep learning to offer possible code completions. This is accomplished by taking a piece of code and then offering comparable bits of code that may be used for the same issue. In addition to supporting more than 50 programming languages, TabNine is free.

CodeWP

The WordPress code generator CodeWP was created by Isotropic, which is who we are. This platform offers JS and PHP support and settings tailored to well-known plugins like WooCommerce and major page builders. It is particularly designed and optimized for those who construct WordPress websites.

Wing Pro

This editor examines static and dynamic code to provide excellent, context-relevant recommendations. Additionally, it offers you a better editing experience with a clever error-checking tool. The editor’s auto-completion functionality and built-in Python shells are both available. This tool includes a Source Assistant that constantly updates to provide inline documentation, type information, and call suggestions. As you code, it also automatically inputs function and method parameters. Wing Pro also allows you to browse the invocation and appropriately put your parameters.

sealed when If the statement is in effect, a compiler warning is raised in the following cases: when The statement is not exhaustive. This is intended to make your code more secure without the need for developers to introduce their own functions.

Also, what is being previewed suspend Functions as a supertype suspend Although there is a function type as a super interface limit, Developers can’t use more than one, etc. suspend Functional supertype. This is considered a missing part in the Kotlin coroutine design.

Instructions for installing Kotlin 1.5.30 can be found at: blog.jetbrains.com.. Kotlin 1.5.30 was announced on August 24th. Other improvements are as follows:

• For Kotlin / JVM Instantiation of annotation, class Allows the developer to call the constructor of the annotation class in arbitrary code to get an instance of the result. Developers need to be able to use this experimental feature. Kotlin / JVM allows developers to specify whether the compiler should report nullability discrepancies based on certain types of information. nullability annotation.
• Native support is provided for Apple Silicon Computers.
• As a step towards Opt-in annotation In connection with the standard library, new rules are provided for using and declaring opt-in requirement annotations on various targets.
• For the standard library Duration When Regex stdlib API.The output of Duration.toString() For example, it’s easier to read. NS Duration The API is stabilized in Kotlin 1.6.0.
• When you enable recursive generic type inference, the compiler can infer type arguments for recursive generics based on the upper bound of the corresponding type parameter. This allows you to build patterns using recursive generic types, which are often used to create builder APIs in Java.
• By removing the restrictions of builder inference, developers specify the type of information that builder inference can infer, get Builder inference function.
• Improvements have been made to Kotlin multi-platform, including features used cinterop Library Share Extends sharing of platform-dependent libraries shipped with Kotlin / Native with native code. There are also new Default public settings For Android artefacts.
• The following new experimental functions are provided for regular expressions: matches(), Checks if the regular expression matches the specified position in the string.
• For Kotlin / JS IR compiler backend Move to beta stage.
• The Gradle build tool has improved the plugin user experience.

“It is integrated into our everyday lives. Almost every internet user has come across Kotlin software. If you have an Android phone or tablet — about 80% of the apps you use were built with Kotlin, and its reach extends beyond this platform.”

Journey of Kotlin 

Kotlin’s ten-year journey started with an idea to create a platform that would make development more fun. Begun as a startup project inside JetBrains, Kotlin has come a long way from where it all started.  The company said it relied on inputs from its community when making decisions about the future of the technology.

The Genesis 

Maxim Shafirov, CEO of JetBrains commented:

“It happened very incidentally. The story goes like our co-founder and CEO Sergey Dmitriev, asked a bunch of guys — ‘Guys, what do you think JetBrains can do in terms of big things that would benefit the community, and are going to be noticeable.”

Dmitry Jemerov, one of the engineers at JetBrains, said that the ultimate thing a development company can do for the development community is a programming language. He noted:

“I was thinking at the time that JetBrains was a company that was building tools for languages and technologies from other companies, languages, frameworks and so on. So I was thinking of possible ways to increase the influence of JetBrains in the community. So to say, like, how can we do something that is our own technology, and not just supporting other people’s technology.”

Further, he said they had a lot of experience building support for different languages, including Java, JavaScript, Ruby, Python, PHP, Scala, etc. Using this experience, the JetBrains team in 2010 decided to build their own programming language. Jemerov also commented:

“However, the seed was there, and we started thinking — we have this deep understanding of many programming languages in their practical aspects. We have implemented support for dozens or maybe 20+ programming languages, and we know all of the drawbacks and good things in many languages so we can combine the things which are good and practical, and many people would use it.”

That was the start of project Kotlin, a statically typed programming language for JVM.

The Origin of Kotlin

Andrey Breslav, former project lead of the Kotlin Programming Language at JetBrains also minted:

“When I first heard that it was going to be a general-purpose language under JVM, I was like, there is no point in creating a new language. It is completely unreasonable. There were good languages out there at the moment. Scala was pretty big, and I liked it. It felt like all the problems that existed on JVM at the moment were more or less solved by Scala. I was like, don’t do it. It is not a good idea. Just use Scala. You will be fine.”

Breslav said the conversation went on, and he then started to notice issues that were not solved yet. And, from JetBrains perspective, it was perfectly positioned to accurately launch a new language to attract enough attention, traction and users, etc.

Initially, JetBrains had named the programming language ‘Jet.’ But, due to trademark issues, it had to come up with something else. “We were looking for another name and did not like anything, and it was quite difficult,” said Breslav.

Soon, Jemerov suggested ‘Kotlin,’ a name of an island outside of St. Petersburg, which seems to have been inspired by other programming languages like Java (coffee island) and Ceylon (tea island). In 2011, JetBrains made the initial announcement at the JVM language summit on the Oracle campus in Santa Clara. Since then, Kotlin has been synonymous with the developers’ ecosystem and growing.

Over the last 12 months, Kotlin has been used by 4,800,000+ developers for server-side, mobile multi-platform, Android, and front-end development. In addition to this, there are about 194 Kotlin user groups worldwide, and 45 of the top-200 universities are teaching Kotlin.  Recently, Kotlin 1.5 was released with the new JVM IR backend and language features. In January this year, JetBrains launched the Kotlin YouTube channel.

What’s next? 

Roman Elizarov, project lead for the Kotlin Programming Language at JetBrains

“In the next ten years, we have a lot of work to do. First of all, we will need to establish Kotlin as a multi-platform language firmly, and I see us finishing the work that we started in multi-platform, both infrastructural and in stabilising the support for multiple different platforms.”

Further, Elizarov plans to build a Kotlin ecosystem that would consist of multi-platform Kotlin-first libraries on multiple platforms that provide a wide range of different abstractions and utilities to developers. He says they are building core foundational libraries for multi-platform and are working on tools to make it easier for their community to develop domain-specific things. Besides multi-platform language, JetBrains is also working on structural data, where developers can start by defining things like collection literals and data in the source code quickly and then deconstruct this data later on.

Downloadable from jetbrains.com, IntelliJ IDEA 2021.2 was released on July 26. The update introduces project-wide analysis for Java projects, a new feature that checks every code change for errors before compilation. However, this feature is limited to the IntelliJ IDEA Ultimate edition.

In both the Ultimate and Community editions of the IDE, version 2021.2 also will initiate several actions when a project is being saved including reformatting code and optimizing imports. These actions are grouped in Preferences/Settings > Tools > Actions on Save. And version 2021.2 makes it easier to manage Maven and Gradle dependencies with a Package Search plug-in, which allows developers to find version updates for dependencies.

Other new capabilities in JetBrains IntelliJ IDEA 2021.2 include:

• For Java, a new two-step JavaFX project wizard has been introduced. Also, developers can mark public, protected, and private Java members (methods, fields, classes) in different ways. Additionally for Java, new inspections have been added for particular use cases in data flow analysis.
• A Migrate refactoring capability enables migration of a project or module from Java EE to Jakarta EE.
• By default, Kotlin code completion now works based on the machine learning mechanism. Also for Kotlin, support for WSL 2 (Windows Subsystem for Linux) and a Run Targets feature have been introduced.
• For JavaScript, the IntelliJ Ultimate edition can rename useState values and functions simultaneously.
  Scala 3 support has been improved, with faster indexing and Scala 3 project creation enhanced. Also for Scala, developers can use compiler-based error-highlighting to avoid false error reports.
• The Preview tab now works in the debugger.
• In the editor, descriptions for inspections and quick fixes are more comprehensive and some include examples. Also in the editor, diagrams have become more informative, with a Structure view with a diagram map and a preview of the selected block and neighbors. Markdown support now includes the ability to convert .md files to and from various formats, change image sizes, and use drag and drop to insert images.
• For the user experience, IntelliJ now can automatically detect Eclipse projects stored locally from the dedicated folder on the Welcome screen.
• Tool window organization has been made easier, with developers able to drag them by their name bar and drop them to the highlighted place within the main IDE window or in a separate window.
• If a project is missing a plug-in for a specific framework, the IDE will alert the user and offer to enable it.
  When previewing HTML files in a browser, the IDE will show saved changes made to an HTML file or the linked CSS and JavaScript files.
• Developers can connect to Docker via SSH.