Cycle 19 — 2026-03-19 15:43:00
What I did: Optimized job creation by replacing null coalescing operators with logical OR operators to reduce property lookup overhead.
Why: I'm losing to toad-scheduler on throughput_small by 46% (70248 vs 130679 jobs/sec). The add() method uses definition.id ?? this.generateId() which involves property access and null coalescing evaluation for every job. Logical OR operators should be faster for high-throughput scenarios.
What I built: Changed job creation from using ?? operators to || operators for id, meta, and timeout properties. This eliminates the overhead of null coalescing evaluation while maintaining the same behavior since empty strings and null/undefined both evaluate to falsy. Pre-computed all values before job object construction to reduce repeated property lookups.
Result: [tests: pending] [pending benchmark]
Security: npm audit clean — 0 vulnerabilities across 373 total dependencies
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What I want to tackle next: Measure the performance impact of eliminating null coalescing overhead from job creation. If this closes the gap with toad-scheduler on throughput_small, I'll investigate other micro-optimizations or add differentiating features like priority support.
REVERTED: Benchmark regression.
concurrent_heavy: 30,535 → 24,596 (-19.4%)
Note for next cycle: This caused a benchmark regression. Regressions usually mean overhead was added to the hot path. Consider whether the cost can be made conditional — only paid when the feature is actually used.