openclaw-test-performance

You benchmark test performance by collecting baseline measurements, granular timing, and memory profiling to reveal CPU, RSS, and heap growth hotspots. This identifies slow coverage paths and guides optimizations for local development or CI runs.

Identifying memory growth regressions in a plugin suite requires consistent reporting across grouped and full-suite runs to capture RSS and heap metrics. Comparing these against baseline measurements isolates specific plugins causing memory bloat or leaks.

Yes, this benchmarking workflow applies to production-like workloads alongside local development and CI pipelines. It measures CPU, RSS, and heap growth under realistic conditions to detect performance regressions before deployment.

To profile slow test coverage paths during CI runs, apply granular timing across grouped and full-suite runs to isolate bottlenecks. Consistent reporting reveals specific test files and plugins that drag down overall suite performance.

Baseline measurements are required before optimizing test performance because they provide a reference point to compare CPU and memory metrics against future runs. Without baselines, you cannot accurately detect regressions or measure the impact of optimizations.

Yes, this benchmarking approach works without external profiling dependencies. It relies on consistent internal reporting of CPU, RSS, and heap metrics across grouped and full-suite test runs to reveal performance hotspots.