To refactor a legacy Java module, Atlas closes the gap that makes refactors dangerous: silent breakage at a callsite nobody knew about. Atlas maps the module's public surface with the lsp tool's documentSymbol operation, runs findReferences on every exported symbol to enumerate the callers, pins the green baseline with JUnit 5 via mvn test, and only then restructures with apply_patch, which anchors on context lines and refuses to apply against a drifted file.
How do I refactor a legacy Java class without breaking its callers?
Atlas enumerates the callers first. The lsp tool's documentSymbol operation maps the legacy Java module's public surface, then findReferences on each exported symbol lists every callsite across your Maven modules. Nothing in src/main/java is touched until that list exists and a green JUnit 5 baseline from mvn test is recorded.
The risk in a Java refactor is not the class you are editing, it is the class three packages away that calls a protected method you assumed nobody used. Reflection, dependency injection, and interface implementations all hide callers from a casual read. Because Atlas indexes code by AST declarations using tree-sitter, not blind line windows, the module's methods and fields come back as real declarations, and the language server's findReferences returns the true reference set rather than a text match. The refactor is scoped by evidence rather than by optimism.
Why should I run JUnit tests before starting a Java refactor?
Atlas pins behavior before changing it: running the existing suite with JUnit 5 via mvn test and recording the green baseline is step two, not step ten. A legacy Java module with three already-failing tests will otherwise make every later failure look like your fault.
A baseline is what turns a refactor into a measurable operation. Atlas runs mvn test through the bash tool, which records the process exit code in its metadata alongside the output, so the green state is a fact rather than an impression from scrolling Maven output. The baseline also reveals what the legacy Java module is actually tested for, which is usually less than you hope: a class with a single happy-path JUnit test is a class where a structural change needs new tests before it needs new structure.
How does apply_patch make a Java restructure safer than an edit chain?
Atlas restructures Java with apply_patch, which seeks each hunk's context and old_lines and fails with Failed to find context if the file has drifted. A patch against src/main/java/com/example/legacy/OrderService.java that no longer matches the file refuses to apply, and JUnit 5 via mvn test re-runs after each hunk lands, not once at the end.
Chaining a dozen edits across a 2000 line legacy Java class is how a refactor corrupts a file: each edit shifts the lines the next one assumed. apply_patch anchors on context, so a drifted file produces a loud Failed to find context error instead of a silently misplaced hunk. Atlas computes a unified diff for every file edit and surfaces it for approval before writing, so a change to a Java class hierarchy is reviewed rather than assumed, and Atlas snapshots file changes as git patches so an unwanted structural change can be diffed and rolled back.
How often should I run mvn test during a Java refactor?
Atlas re-runs the tests with JUnit 5 via mvn test after each hunk lands, not once at the end. A legacy Java refactor that breaks on the seventh hunk is trivially diagnosed when hunks one through six were green, and nearly untraceable when all twelve landed together.
Frequent verification is cheap compared with bisecting a broken module by hand. Maven resolves the dependency set from pom.xml, so each mvn test run exercises the same classpath the build server will use. Atlas's bash tool is a real shell, so running a single test class or the whole suite is just a matter of which Maven invocation you approve. Every Atlas tool call is permission-gated against allow, ask, and deny rules before it runs, so the test runs and the patches are each checked before they happen.
How do I track a partially migrated Java module?
Atlas tracks the remaining callsites in a todowrite list so a partially migrated Java module cannot be mistaken for a finished one. Each callsite that findReferences turned up is either migrated and re-proved with JUnit 5 via mvn test, or still open on the list, rather than something you rediscover during code review.
Half-finished refactors are the worst outcome, because the codebase now carries both the old shape and the new one. A todowrite list holding every unmigrated callsite, keyed to the file and the symbol, is what turns a long Java migration into a resumable one across sessions. Running Spotless over the touched files keeps the diff limited to structure rather than formatting, and Atlas reads git branches, status, and diffs, so what has actually changed in the Maven module is visible at every point.
Step by step
- 01Run atlas in a project with a pom.xml or build.gradle and let Atlas read your packages, classpath, and build configuration.
- 02Map the legacy module's public surface with the lsp tool's documentSymbol operation, then run findReferences on each exported symbol to enumerate every callsite.
- 03Pin behavior first: run the existing tests with JUnit 5 via mvn test through bash and record the green baseline before changing anything.
- 04Restructure with apply_patch, which seeks each hunk's context and old_lines and fails with Failed to find context if the Java file has drifted.
- 05Review the unified diff Atlas surfaces for each Java file before it is written.
- 06Re-run JUnit 5 via mvn test after each hunk lands, not once at the end, with Maven resolving the classpath from pom.xml.
- 07Track the remaining callsites in a todowrite list so a partially migrated module cannot be mistaken for a finished one.
- 08Run Spotless over the touched files so the final diff shows structure, not formatting.
Frequently asked questions
- how to refactor a legacy java class without breaking callers
- Have Atlas run the lsp tool's documentSymbol to map the module's public surface, then findReferences on each exported symbol to enumerate every callsite across your Maven modules before anything is edited.
- can an AI agent find all callers of a java method including reflection-free indirect uses
- Atlas uses the language server through its lsp tool, so findReferences returns the true reference set rather than a text match. Grep is still useful for strings and config the type system does not see.
- why does atlas use apply_patch for java refactors
- apply_patch seeks each hunk's context and old_lines and fails with Failed to find context if the file has drifted, which prevents a misplaced hunk in a long legacy Java class that a chain of edits would cause.
- how do i keep a large java refactor reviewable
- Land one hunk at a time, run JUnit 5 via mvn test after each, and track unmigrated callsites in a todowrite list. Atlas computes a unified diff for every file edit and surfaces it for approval before writing.
- what does atlas need to work on a java project
- Run atlas in a project with a pom.xml or build.gradle. Atlas reads your packages, classpath, and build configuration, then can add JUnit tests or refactor a class hierarchy with the diff shown for review.
- does atlas run spotless on java code
- Atlas can run Spotless through its bash tool over the files it touched, so the refactor diff shows structural changes rather than formatting churn.
- how do i undo a java refactor atlas applied
- Atlas snapshots file changes as git patches, so edits can be diffed and rolled back. Atlas also reads git branches, status, and diffs, so the state of the Maven module is visible at every step.
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