How does Atlas ensure my Groovy tests don't break during refactoring?

Atlas ensures your Groovy tests don't break by first running `atlas bash ./gradlew test` to establish a green baseline. After each incremental change applied via `apply_patch`, Atlas immediately re-runs `gradle test` to verify that your Spock specifications still pass, catching regressions instantly.

Can Atlas handle refactoring Groovy code within a `Jenkinsfile`?

Yes, Atlas can handle refactoring Groovy code within a `Jenkinsfile`. Its `lsp` tool can find references and symbols within Groovy DSLs, and `apply_patch` can modify these files, ensuring consistency across your build and pipeline scripts.

What if my Groovy file has changed since Atlas planned the refactor?

If your Groovy file has changed, Atlas's `apply_patch` tool will detect the drift. It anchors on context lines and old lines, and if these do not match, it will fail with 'Failed to find context', preventing the patch from being applied incorrectly.

How does Atlas help maintain Groovy code style during refactoring?

Atlas helps maintain Groovy code style by integrating with `Spotless`. After making structural changes, Atlas can be prompted to apply `Spotless` with the Groovy formatter to the modified files, ensuring adherence to your project's defined style guidelines.

Is my Groovy code sent to third-party servers when using Atlas?

No, your Groovy code is not sent to third-party servers. Atlas can build its code index with local Ollama embeddings, keeping your proprietary Groovy code securely on your local machine.

How does Atlas track all the places a Groovy method is called?

Atlas tracks all callsites for a Groovy method using its `lsp` tool's `findReferences` operation. This leverages the language server to precisely enumerate every location where a specific Groovy symbol is invoked, across all relevant files.

Can I review the changes Atlas makes to my Groovy files?

Absolutely. Atlas computes a unified diff for every file edit it proposes to your Groovy codebase and surfaces it for your approval before writing. You have full control to review and accept or reject any change.

Refactor a Legacy Groovy Module with Atlas in 2026

In 2026, Groovy developers can refactor legacy modules without fear of silent breakage by pairing Atlas with their existing toolchain, including Spock (gradle test) for robust testing, Gradle for dependency management, and Spotless for consistent formatting. Atlas ensures behavior preservation and caller compatibility throughout the restructuring process by mapping public surfaces, pinning behavior with tests, and applying changes incrementally.

How Atlas Maps a Groovy Module's Public Surface

Atlas identifies a Groovy module's public surface in 2026 by leveraging its `lsp` tool, which queries the language server for `documentSymbol` operations. This process enumerates all exported symbols within files like `src/main/groovy/com/example/LegacyModule.groovy`.

Before any refactoring begins, Atlas uses its `lsp` tool to map the public surface of your Groovy module. This is crucial for understanding all external touchpoints. By invoking `lsp documentSymbol` on your Groovy source files, Atlas builds a comprehensive list of all classes, methods, and fields declared within the module. For each identified symbol, Atlas then performs a `findReferences` operation, meticulously enumerating every single callsite across your entire codebase. This includes references within other Groovy classes, Gradle build scripts (`build.gradle`), or even Jenkins pipeline scripts (`Jenkinsfile`). This initial mapping ensures that Atlas has a complete understanding of all potential callers, mitigating the risk of silent breakage during the refactoring process.

Pinning Groovy Module Behavior with Spock and Gradle

Atlas ensures a Groovy module's behavior remains unchanged during refactoring by first pinning its current state with existing Spock specifications. In 2026, Atlas executes these tests using the `bash` tool with the `gradle test` command, recording a green baseline.

A core principle of safe refactoring is to 'pin' the existing behavior before making any changes. For Groovy projects, this means running your Spock specifications. Atlas achieves this by using its `bash` tool to execute the standard `gradle test` command. This command compiles and runs all Spock specifications found in `src/test/groovy`, providing a clear, green baseline of expected behavior. Atlas records this baseline, and crucially, re-runs `gradle test` after each incremental change. This immediate feedback loop, powered by Spock's expressive `given`, `when`, and `then` blocks, ensures that any unintended behavioral shifts are caught instantly, preventing regressions from accumulating and becoming difficult to diagnose later in the refactoring process.

Applying Structural Changes to Groovy Code with Atlas

Atlas applies structural changes to Groovy code using its `apply_patch` tool, which anchors on context lines to ensure precise modifications. This method prevents accidental changes to drifted files, a common risk in 2026's evolving codebases.

Once the public surface is mapped and behavior is pinned, Atlas proceeds with structural changes using its `apply_patch` tool. This tool is designed for robust and safe code modification. Instead of blindly applying changes, `apply_patch` seeks each hunk's context and old lines within the target Groovy file. If the file has drifted or changed unexpectedly since the patch was generated, `apply_patch` will fail with a 'Failed to find context' error, preventing a potentially destructive modification. This ensures that refactoring operations, such as moving a method from one Groovy class to another or converting a nested closure to a typed method, are applied only when the file's state matches expectations. Atlas also computes a unified diff for every file edit and surfaces it for approval, giving you full control over what changes are written to your `src/main/groovy` files.

Ensuring Groovy Code Quality with Spotless and Git

Atlas integrates with Groovy's `Spotless` formatter to maintain code quality and consistency throughout the refactoring process. In 2026, Atlas can apply `Spotless` with the Groovy formatter to touched files, ensuring adherence to project style guides.

Maintaining code quality and consistency is paramount during refactoring. Atlas direct integrates with your Groovy project's `Spotless` configuration. After applying structural changes, Atlas can be prompted to apply `Spotless` to the modified Groovy files. This ensures that all newly structured code adheres to your project's formatting standards, preventing style inconsistencies from creeping in. Furthermore, Atlas leverages Git for robust version control. It reads Git branches, status, and diffs, and can stage and create commits on your behalf. Every file edit is snapshotted as a Git patch, allowing changes to be easily diffed, reviewed, and rolled back if necessary, providing an additional layer of safety and auditability for your Groovy codebase.

Tracking Groovy Refactoring Progress with Atlas's todowrite

Atlas helps manage the complexity of refactoring a Groovy module by tracking remaining callsites with its `todowrite` tool. This ensures that a partially migrated module is never mistaken for a finished one, a critical safeguard in 2026's large projects.

Refactoring a large Groovy module often involves migrating numerous callsites. Atlas provides the `todowrite` tool to manage this process effectively. After identifying all references to a symbol using `lsp findReferences`, Atlas can generate a `todowrite` list containing all remaining callsites that need to be updated. As you migrate each callsite, you can mark it off the list. This systematic approach ensures that no callsite is overlooked, and the refactoring effort remains transparent and trackable. The `todowrite` list acts as a living checklist, preventing the premature declaration of a refactoring task as complete when outstanding migrations still exist, especially important when dealing with complex Groovy DSLs or shared pipeline libraries.

Step by step

01Run Atlas in your Groovy project, ensuring it can read your `build.gradle` or `Jenkinsfile` to index your codebase.
02Map the module's public surface: Use `atlas lsp documentSymbol` on your Groovy source files (e.g., `src/main/groovy/com/example/MyModule.groovy`) to identify all exported symbols.
03Enumerate callers: For each identified symbol, run `atlas lsp findReferences` to list every callsite across your Groovy project, including those in `build.gradle` or `Jenkinsfile`.
04Pin behavior: Execute existing Spock specifications with `atlas bash ./gradlew test` and record the green baseline before making any changes to your Groovy code.
05Restructure incrementally: Apply structural changes to your Groovy files using `atlas apply_patch`, ensuring each hunk anchors correctly on context lines.
06Verify behavior: After each `apply_patch` operation, re-run `atlas bash ./gradlew test` to immediately confirm that the Groovy module's behavior remains unchanged.
07Track remaining work: Use `atlas todowrite` to manage the list of remaining callsites that need migration, ensuring no Groovy caller is left unaddressed.
08Format code: Have Atlas apply `Spotless` with the Groovy formatter to touched files using `atlas bash ./gradlew spotlessApply` (or similar command) to maintain code style.
09Review and commit: Approve Atlas's proposed changes via its unified diff, then let Atlas stage and create a Git commit for the refactored Groovy code.

Frequently asked questions

How does Atlas ensure my Groovy tests don't break during refactoring?: Atlas ensures your Groovy tests don't break by first running `atlas bash ./gradlew test` to establish a green baseline. After each incremental change applied via `apply_patch`, Atlas immediately re-runs `gradle test` to verify that your Spock specifications still pass, catching regressions instantly.
Can Atlas handle refactoring Groovy code within a `Jenkinsfile`?: Yes, Atlas can handle refactoring Groovy code within a `Jenkinsfile`. Its `lsp` tool can find references and symbols within Groovy DSLs, and `apply_patch` can modify these files, ensuring consistency across your build and pipeline scripts.
What if my Groovy file has changed since Atlas planned the refactor?: If your Groovy file has changed, Atlas's `apply_patch` tool will detect the drift. It anchors on context lines and old lines, and if these do not match, it will fail with 'Failed to find context', preventing the patch from being applied incorrectly.
How does Atlas help maintain Groovy code style during refactoring?: Atlas helps maintain Groovy code style by integrating with `Spotless`. After making structural changes, Atlas can be prompted to apply `Spotless` with the Groovy formatter to the modified files, ensuring adherence to your project's defined style guidelines.
Is my Groovy code sent to third-party servers when using Atlas?: No, your Groovy code is not sent to third-party servers. Atlas can build its code index with local Ollama embeddings, keeping your proprietary Groovy code securely on your local machine.
How does Atlas track all the places a Groovy method is called?: Atlas tracks all callsites for a Groovy method using its `lsp` tool's `findReferences` operation. This leverages the language server to precisely enumerate every location where a specific Groovy symbol is invoked, across all relevant files.
Can I review the changes Atlas makes to my Groovy files?: Absolutely. Atlas computes a unified diff for every file edit it proposes to your Groovy codebase and surfaces it for your approval before writing. You have full control to review and accept or reject any change.

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