Performance optimization requires developing intuition about where it matters most. Start by estimating operation costs across different speed tiers (cache, RAM, disk, network) to make informed architectural decisions. Always measure with profiling tools before optimizing, as intuition about bottlenecks is often wrong. The biggest wins come from better algorithms and data structures (O(N) vs O(N²)). Memory layout matters significantly due to CPU cache behavior—prefer contiguous storage and sequential access. Reduce allocations through pre-sizing containers, reusing objects, and moving instead of copying. Avoid unnecessary work through fast paths for common cases, caching, lazy evaluation, and early bailouts. Focus optimization efforts on the critical 20% of code that accounts for 80% of runtime, balancing performance gains against code complexity and maintainability.
Table of contents
😘 Kiss bugs goodbye with fully automated end-to-end test coverage (Sponsored)Learning to EstimateMeasure Before We OptimizeAlgorithmic WinsMemory MattersReduce AllocationsAvoid Unnecessary WorkPractical Tips for Everyday CodingKnowing When to StopConclusionSort: