Interview Questions
Optimization strategies: 1) Use beforeAll when possible, 2) Minimize per-test setup, 3) Implement efficient cleanup, 4) Share setup where appropriate, 5) Cache test resources.
Caching impacts: 1) Test result caching, 2) Module caching, 3) Transform caching, 4) Resource caching, 5) Cache invalidation strategies. Proper caching improves performance.
Distributed testing: 1) Test network latency, 2) Measure data consistency, 3) Monitor system throughput, 4) Test scalability, 5) Benchmark distributed operations.
Test profiling: 1) Use Node.js profiler, 2) Implement custom profilers, 3) Track execution paths, 4) Measure function calls, 5) Analyze bottlenecks.
Identifying slow tests: 1) Use --verbose flag, 2) Implement custom timing reporters, 3) Monitor test execution times, 4) Set timing thresholds, 5) Use test profiling tools. Helps optimize test suite performance.
Capacity testing: 1) Measure maximum load, 2) Test resource limits, 3) Monitor system boundaries, 4) Test scaling limits, 5) Benchmark capacity handling.
Data processing: 1) Test large datasets, 2) Measure processing speed, 3) Monitor memory usage, 4) Test batch processing, 5) Benchmark algorithms.
Memory measurement: 1) Use process.memoryUsage(), 2) Track heap snapshots, 3) Monitor garbage collection, 4) Measure memory leaks, 5) Implement memory thresholds.
Database testing: 1) Measure query performance, 2) Test connection pooling, 3) Monitor transaction speed, 4) Test concurrent access, 5) Benchmark CRUD operations.
I/O performance: 1) Measure read/write speeds, 2) Test concurrent operations, 3) Monitor file system usage, 4) Test streaming performance, 5) Benchmark file operations.
Load testing: 1) Simulate user load, 2) Measure system response, 3) Monitor resource usage, 4) Test concurrent users, 5) Benchmark load handling.
Cache performance: 1) Measure hit rates, 2) Test cache efficiency, 3) Monitor cache size, 4) Test eviction policies, 5) Benchmark cache operations.
Memory leak testing: 1) Track object retention, 2) Monitor heap growth, 3) Test long-running operations, 4) Implement cleanup verification, 5) Use memory profiling tools.
Resilience testing: 1) Test failure recovery, 2) Measure degraded performance, 3) Test circuit breakers, 4) Monitor system stability, 5) Benchmark recovery operations.
Measuring execution time: 1) Use jest.useFakeTimers(), 2) Use console.time/timeEnd, 3) Implement custom timing decorators, 4) Use performance.now(), 5) Configure Jest's verbose timing option. Example: const start = performance.now(); /* test */ const duration = performance.now() - start;
Parallelization impacts: 1) Reduced total execution time, 2) Increased resource usage, 3) Potential test interference, 4) Worker process management, 5) Load balancing considerations.
Regression testing: 1) Track performance metrics, 2) Compare against baselines, 3) Detect performance degradation, 4) Monitor trends, 5) Implement automated checks.
Test timeout configuration: 1) Set global timeout in config, 2) Set individual test timeouts, 3) Balance timeout vs expected performance, 4) Handle slow tests appropriately, 5) Monitor timeout failures for performance issues.
Basic metrics include: 1) Test execution time, 2) Setup/teardown time, 3) Memory usage, 4) Number of assertions, 5) Test suite duration. Important for establishing baselines.
Common bottlenecks: 1) Large test setups, 2) Excessive mocking, 3) Unnecessary test repetition, 4) Poor test isolation, 5) Inefficient assertions. Identify and optimize these areas.
Network testing: 1) Measure request latency, 2) Test concurrent requests, 3) Simulate network conditions, 4) Monitor bandwidth usage, 5) Test connection pooling.
Async performance testing: 1) Measure async operation duration, 2) Track concurrent operations, 3) Monitor resource usage, 4) Test throughput capabilities, 5) Handle timeouts appropriately.
Optimization testing: 1) Identify bottlenecks, 2) Measure improvement impact, 3) Test optimization strategies, 4) Monitor resource efficiency, 5) Benchmark optimizations.
Microservice testing: 1) Test service communication, 2) Measure service latency, 3) Monitor resource usage, 4) Test service scaling, 5) Benchmark service operations.
Benchmark implementation: 1) Define performance baselines, 2) Create benchmark suites, 3) Measure key metrics, 4) Compare against standards, 5) Track performance trends.
Resource testing: 1) Monitor CPU usage, 2) Track memory consumption, 3) Measure I/O operations, 4) Test concurrent processing, 5) Implement resource limits.
Advanced monitoring: 1) Custom metric collection, 2) Performance dashboards, 3) Trend analysis, 4) Alert systems, 5) Performance regression detection.
Scalability testing: 1) Measure load handling, 2) Test resource scaling, 3) Monitor performance degradation, 4) Test concurrent operations, 5) Benchmark scaling operations.
Rendering performance: 1) Measure render times, 2) Track re-renders, 3) Monitor DOM updates, 4) Test large datasets, 5) Profile component lifecycle.
Real-time testing: 1) Measure response times, 2) Test event processing, 3) Monitor message latency, 4) Test concurrent users, 5) Benchmark real-time operations.