Parallel Testing

Parallel testing distributes design system test execution across multiple processes or machines. Implementing parallel testing dramatically reduces total testing time by leveraging available computing resources.

What Is Parallel Testing

Parallel testing runs multiple tests simultaneously rather than sequentially. Instead of running tests one after another, parallel testing executes independent tests at the same time across available resources. This converts sequential time into parallel time.

Parallel testing becomes particularly valuable as test suites grow. Large suites that would take hours sequentially can complete in minutes with sufficient parallelization. This enables comprehensive testing without prohibitive time costs.

How Parallel Testing Works

Test independence ensures tests can run simultaneously. Tests must not depend on shared state that creates conflicts. Independent tests can run in any order without affecting results. Dependency elimination enables parallelization.

Work distribution assigns tests to available workers. Distribution strategies include round-robin, load balancing based on expected duration, or grouping related tests. Effective distribution maximizes resource utilization.

Result aggregation collects outcomes from parallel workers. Results must be gathered, organized, and reported coherently. Failure handling must work correctly when tests fail in parallel.

Resource management provides workers with needed resources. This includes compute resources, test fixtures, and any external dependencies. Resource contention must be managed to prevent interference.

Key Considerations

• Tests must be independent to run in parallel
• Distribution strategies affect efficiency
• Resource requirements scale with parallelization
• Flaky tests become more problematic with parallelization
• Infrastructure must support desired parallelization level

Common Questions

What prevents tests from running in parallel?

Shared state prevents parallelization. Tests that modify global state, share database records, or depend on ordering cannot run safely in parallel. Eliminating shared state enables parallelization.

How many parallel workers are optimal?

Optimal worker count depends on available resources and test characteristics. More workers help until resources saturate or overhead dominates. Experimentation identifies the optimal level for specific contexts.

How do parallel tests handle shared resources?

Shared resources require isolation strategies. Separate database schemas, unique test data, or resource locking prevent conflicts. Some organizations avoid shared resources entirely through mocking or containerization.

Summary

Parallel testing reduces total testing time by running independent tests simultaneously. Success requires test independence, effective distribution, and appropriate resource management. Organizations should implement parallel testing to make comprehensive test suites practical.