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June 11, 2024

Java Basics: Your Guide to AI in Java IDEs

Developer Productivity

Artificial Intelligence, or AI, is revolutionizing many aspects of technology, and Integrated Development Environments (IDEs) for Java are no exception. By integrating AI capabilities, modern Java IDEs are transforming the way developers write and debug their code, enhancing productivity, and improving code quality.  

Read on to discover how AI is being leveraged in Java IDEs to streamline development processes and elevate the overall coding experience. We’ll also cover AI assistants integrated in Java IDEs, including IntelliJ IDEA and Microsoft Visual Studio Code (VSCode).  


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How Does Generative AI Write Java?

Generative AI writes Java code based on user input and Natural Language Learning models. The user completes a prompt about what they want the code to do in plain language, and the generative AI tool will return Java code that addresses the requirements set forth in the prompt.  

Why Use AI to Write Java?

Like a lot of other applications of AI, AI code generators can accelerate simple-but-time-consuming tasks. Most Java developers can write boilerplate code in their sleep—but it still takes precious time.  

By using AI to assist with basic but time-consuming tasks, developers can put their brain power toward more complex tasks like debugging and coming up with new features.  

Downsides to Using AI Code Generators

AI code generators create code based on learning models from other code samples. That means errors or intricacies may be inadvertently copied, too. There may also be concerns around intellectual property and sensitive information.  

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Use Cases for AI in Java Development

AI might not be able to write an entire Java application from start to finish (yet), but it can help automate some of the more tedious processes or augment tasks that are prone to error. Read on to learn more about use cases where AI is lending a productivity advantage, including intelligent code completion, debugging, and code refactoring.  

Intelligent Code Completion

Intelligent code completion is an autocomplete feature that suggests lines of code based AI suggestions based on compiled libraries. 

One of the most notable applications of AI in Java IDEs is intelligent code completion. Traditional IDEs have offered basic autocomplete features for years, but AI-powered IDEs take this a step further. These tools analyze the context of the code, understand the developer's intent, and provide accurate and relevant contextual code suggestions.  

AI algorithms can predict the next lines of code, complete statements, and even suggest entire blocks of code based on the patterns and structures detected in the existing codebase. 

Error Detection and Bug Fixing

Developers typically spend much of their time identifying and fixing errors that come up in their application. AI-driven error detection and bug fixing are transforming how developers handle these issues.  

Traditional static code analyzers, like Klocwork, identify many common issues in their application, but AI-enhanced tools can detect more complex problems by learning from a vast dataset of coding errors and fixes. These tools can identify potential bugs, suggest fixes, and even apply corrections automatically. 

Refactoring and Code Optimization  

AI-powered code refactoring works by identifying areas that need refactoring and suggesting optimal ways to restructure the code. 

Refactoring code is an essential practice for maintaining a clean and efficient codebase and is frequently used by developers. These tools will analyze the code’s dependencies, detect redundant or inefficient code segments, and recommend improvements.   

IntelliJ employs AI for code optimization, offering suggestions to enhance performance and maintainability. The AI models can detect suboptimal coding practices and suggest more efficient alternatives, ensuring that the code adheres to best practices. 

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IDE-Based AI Code Generators in Java IDEs

AI code generators can come in many forms, including browser-based tools like ChatGPT and integrated IDE-based code generators.  

There are some key advantages of using an IDE-based AI code generator—the most important being that the Java developer doesn’t need to break their flow, leave the IDE, or rely on copious amounts of copy/paste.  

Looking to save more time within you Java IDE of choice? Try JRebel for free for 14 days.  

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JetBrains AI in IntelliJ IDEA

IntelliJ IDEA is the most popular Java IDE, and for good reason: it's loaded with features that help Java developers save time and write better code.  

JetBrains AI gives new power to all of the company’s IDEs—including its flagship Java IDE, IntelliJ IDEA. Moreover, JetBrains AI is included in a supplemental feature in Fleet (currently in Beta).  

Because the AI tool is baked into the IDE, it has contextual awareness of your development environment in a way that external AI code generators do not. I.e., Java developers can ask short questions instead of typing detailed prompts or copy/pasting code fragments.  

For example, IntelliJ IDEA uses AI to offer advanced code completion. Its machine learning models are trained on a vast amount of open-source code, allowing it to provide context-aware suggestions that go beyond simple syntax completion. 

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GitHub CoPilot in Microsoft VSCode

The GitHub Copilot extension in VSCode requires an active subscription to GitHub Copilot, which is one of the leading AI tools for a variety of IDEs and languages. 

GitHub Copilot in VSCode offers several features, including: 

  • Offering developers to get inline code suggestions while they’re writing and iterating code
  • Fixing errors in code
  • Resolving errors while running commands in the terminal
  • Asking questions to help ramp-up on a new code base
  • Using chat features to configure your VSCode setup 

📚 Further Reading:All you need to know about the VSCode extension for JRebel 

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AI in Eclipse

While Eclipse has fallen in popularity over the years, it still holds a leading role in 23% of Java development shops, according to the 2024 Java Developer Productivity Report 

Eclipse has integrated AI capabilities to enhance its error detection features. This feature is used by analyzing code patterns and comparing them against known bug patterns, allowing Eclipse developers more precise and actionable insights. Eclipse also offers several plugins that lend AI functionality, including Tabnine, aiXcoder, and Remain Ai Chat 

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Final Thoughts

 Using AI to accelerate Java code development is just one tool in your broader development toolbox to save time. By eliminating redeploys with JRebel, you can compound the time savings possible with AI integrations in Java IDEs. 

See how much time you can save during your 14-day free trial of JRebel 


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