BitDive
Bitdive provides Regression Safety for Java applications without the hassle of writing mock scripts. Instead of coding tests manually, you simply select real request flows to build versionable Replay Plans.
Cost / License
- Freemium (Subscription)
- Proprietary
Platforms
- Online
- Software as a Service (SaaS)
Features
- Regression testing
- QA Automation
Tags
- replay-testing
- contract-testing
- integration-testing
- junit
- Java
BitDive information
What is BitDive?
Bitdive provides Regression Safety for Java applications without the hassle of writing mock scripts. Instead of coding tests manually, you simply select real request flows to build versionable Replay Plans. Build unit replays, integration and regression suites, and contract checks from the same captured scenarios. BitDive isolates dependencies by auto-generating mocks for JDBC, HTTP, Kafka, and gRPC from observed behavior, so tests stay stable across refactors and API changes. BitDive captures application errors and execution details automatically, giving you white-box visibility: cross-service call chains, method parameters and results, exceptions, and SQL queries, so root cause is clear without log archaeology. Setup is fast: add the libraries, paste a UI generated config, and start capturing scenarios in minutes. Run replays locally, in CI/CD, or in staging to validate changes and catch regressions before release.
What you get • Deterministic replay tests from real traffic, not synthetic examples • Automatic mocking for HTTP, JDBC, Kafka, and other dependencies • Fast bug reproduction from a call or trace id, then validate the fix with the same inputs • Behavioral diffs before and after changes, including performance deltas and query volume • Dashboards like service maps and heatmaps to find hot paths and regressions
Why teams choose BitDive AI test generators still produce code you must review and keep in sync with refactors. BitDive avoids that by turning real runtime behavior into stable replays, so regression coverage grows with real usage and stays low maintenance.
Use cases • Release verification and regression suites built from real scenarios • Reproduce production incidents locally and confirm fixes • Catch N+1 queries and performance regressions with proof from before and after traces







