Announcing inline chat in Eclipse with Amazon Q Developer

April 10, 2025

Note: This content was originally published on the AWS Blog and is reproduced here for archival purposes. Please visit the original post for the most up-to-date version.

Earlier today Amazon Q Developer launched inline chat in the Eclipse IDE (in preview). In this post, I’ll walk you through how I’ve been using this powerful new capability to streamline my Java development workflow, from refactoring existing code to optimizing performance-critical methods. Whether you’re a seasoned Eclipse veteran or just getting started, you’ll see how Amazon Q Developer’s advanced AI-driven tools can supercharge your productivity across the entire software development lifecycle.

Background

As a long-time Java developer, I was thrilled when Amazon Q Developer was integrated in Eclipse last year. I’ve been using Amazon Q Developer for a while now, and it has completely transformed my development workflow. When Amazon Q Developer first launched its inline suggestions feature back in 2022, I was blown away by how much it could accelerate my coding tasks. But the addition of a full chat interface in 2023 took things to the next level. Then in 2024 the new inline chat capability allowed me to edit and refactor my code in place. However, inline chat was not available in Eclipse, until today!

The chat interfacein Amazon Q Developer is where I turn when I’m not quite sure how to accomplish a particular task. I love being able to explain the problem I’m trying to solve, or the concept I’m trying to understand, and getting detailed, contextual responses that help point me in the right direction. The AI-generated code snippets and explanations are invaluable when I’m learning something new or tackling a complex challenge. However, when I know how to accomplish a task, I don’t need the explanation I just want the code.

On the other hand, when I’m workingon a well-understood task, I much prefer to use Amazon Q Developer’s inline suggestions. The way it analyzes my existing code and comments to provide relevant, customized completions is just incredible. It lets me work at faster, creating new functionality without having to constantly switch context or hunt for the right syntax. However, while inline suggestions are great for generating new code, I cannot use it to edit existing code.

Now, with the new inline chat feature in Eclipse (in preview), I can easily edit my code in place using Amazon Q Developer. Instead of having to copy/paste code from a separate chat window, I can describe the changes I want to make right in the editor, and Amazon Q Developer will seamlessly integrate the suggested updates into my code base as a diff. It’s great for for refactoring, bug fixing, and maintaining well-documented, easily-readable code. Let’s look at a couple of examples to see how inline chat works in Eclipse.

Refactoring

Imagine that I am the newest member of a development team, and I was tasked with adding unit tests to the OrderProcessor class. However, as I dug into the code base, I realized that the OrderProcessor was tightly coupled to the OrderRepository implementation. Notice the instantiation of the OrderRepository on line 2 in the following image. This made it difficult to write unit tests, as I couldn’t easily swap in a mock repository. I knew I needed to refactor the code to use dependency injection, but the thought of making all of those changes manually was daunting.

Java code showing complete OrderProcessor class implementation with order processing logic, including order validation and persistence methods using IOrderRepository interface.

Fortunately, with Amazon Q Developer’s inline chat in my Eclipse IDE, I didn’t have to tackle this refactor alone. I selected the OrderProcessor class, invoked the inline chat using the keyboard shortcut (CMD + SHIFT + I for macOS, and CTRL + SHIFT + I for Windows). Then I described the change I want: “Refactor this class to use dependency injection so I can mock the OrderRepository in unit tests.” Note that I could have also asked Amazon Q Developer to leverage a specific DI framework, like Hibernate. However, I am going to keep this simple for the blog post.

Java code displaying OrderProcessor class with a prompt to refactor using dependency injection. Shows current implementation with direct instantiation of OrderRepository and validation methods.

Amazon Q Developer quickly analyzed the code and presented me with a suggested change shown in the following image. The change is presented as a diff so I can see what Amazon Q Developer is removing (in red) and adding (in green). After reviewing the changes, I was pleased to see that Amazon Q Developer had introduced a constructor that took an IOrderRepository interface, allowing me to pass in either the concrete implementation or a test double. This would make it a breeze to write comprehensive unit tests for the OrderProcessor. With a quick click to accept the changes, Amazon Q Developer updated my code, saving me valuable time and ensuring the new feature would be built on a solid, testable foundation.

Java code showing OrderProcessor class with dependency injection prompt. Contains processOrder method that validates and saves orders using an IOrderRepository interface. The code includes validation logic and database operations.

In this example, I selected the entire class. However, I can also ask Q Developer to work on a specific portion of the code.

Optimization

While working on the Order class, I noticed that the containsItem method seemed to be running slowly, especially on orders with a large number of line items. I decided to profile the code and sure enough, that method was a hot spot, consuming a disproportionate amount of CPU cycles. I selected the containsItem method, brought up the inline chat, and asked Amazon Q Developer: “This code is running slow, please optimize it.”

Java code displaying Order class with a popup message suggesting optimization. Shows class fields for id, customer, and items, with a containsItem method implementation using a for loop that could be optimized.

Amazon Q Developer quickly analyzed the existing code, which was using a simple for loop to iterate through the list of items, and provided an improved implementation. As shown in the diff, Amazon Q Developer suggested replacing the for loop with a more efficient stream-based approach, using the anyMatch method to determine if the item is present in the order. This change has improved performance, especially for orders with a large number of line items. I reviewed the changes and accepted Amazon Q Developer’s suggestions.

Java code showing Order class with highlighted section suggesting replacement of traditional for loop with Java 8 Stream API. Contains an implementation of containsItem method with both the original loop and a commented stream-based solution.

Amazon Q Developer’s optimization not only improved the performance of the containsItem method, but also made the code more readable and maintainable going forward.

Conclusion

The integration of Amazon Q Developer into the Eclipse IDE (in-preview) has improved my Java development workflow. Whether I’m learning a new concept, generating boilerplate code, or optimizing a performance bottleneck, Amazon Q Developer’s suite of AI-powered tools has become an indispensable part of my development process. The addition of inline chat, in particular, has streamlined my ability to directly interact with the assistant, seamlessly updating my code base without breaking my concentration. If you’re an Eclipse user looking to supercharge your productivity, I highly recommend installing the Amazon Q Developer plugin today.