145-java-refactoring-high-performance

# Java rules for High Performance Identify and apply practical Java high-performance techniques using a measure-first approach, with emphasis on allocation reduction, data layout, concurrency discipline, and evidence-based validation. **What is covered in this Skill?** - Measure-first workflow for Java code optimization - JVM/runtime-aware coding guidance - Allocation reduction techniques with bad/good patterns - CPU hot-path simplification and loop-level efficiency patterns - Concurrency/backpressure and timeout/cancellation discipline - I/O, parsing, and serialization efficiency patterns - Persistence/query and caching strategy guidance - Java-centric decision workflow: keep/revert based on measured impact **Scope:** Practical optimization in application code and APIs. Apply only where profiling indicates real bottlenecks. ## Constraints Performance optimization must be evidence-driven and safe, focused on Java code changes that preserve correctness and maintainability. - **MEASURE-FIRST**: Establish baseline behavior and identify Java code hot paths before optimization - **NO PREMATURE OPTIMIZATION**: Only optimize code paths identified by profiling evidence - **BEFORE APPLYING**: Read the relevant reference(s) for bad/good examples and measurement workflow - **EDGE CASE**: If hotspot evidence is unclear, ask clarifying questions before changing code ## When to use this skill - Review Java code for high performance - Optimize Java hot path - Reduce Java allocations - Improve Java latency - Improve Java throughput ## Workflow 1. **Identify Java hotspot and baseline behavior** Confirm the performance-sensitive Java path and baseline behavior before changing code. 2. **Select the relevant reference(s) by bottleneck** Pick and read only the reference(s) matching the observed hotspot: `references/145-refactoring-high-performance-java-memory-allocation.md` for allocation pressure, primitives vs. wrappers, escape analysis, collection sizing, data layout, and deduplication; `references/145-refactoring-high-performance-java-cpu.md` for CPU-bound hot paths, bit-level parsing, branchless arithmetic, loop unrolling, Unsafe caution, and SIMD/vectorization; `references/145-refactoring-high-performance-java-code-syntax.md` for code shape, lambdas, API return conventions, parsing syntax, I/O strategy, concurrency, and control-flow improvements. 3. **Apply targeted optimizations** Implement minimal, evidence-backed changes scoped to the chosen domain(s): memory/allocation, CPU/low-level, or code shape/control flow (and adjacent concurrency, I/O, and persistence/caching in Java code). 4. **Validate and compare code-level outcomes** Compare before/after behavior and keep only Java code changes with meaningful, verified gains. ## Reference For detailed guidance, examples, and constraints, see: - [references/145-refactoring-high-performance-java-memory-allocation.md](references/145-refactoring-high-performance-java-memory-allocation.md) - [references/145-refactoring-high-performance-java-cpu.md](references/145-refactoring-high-performance-java-cpu.md) - [references/145-refactoring-high-performance-java-code-syntax.md](references/145-refactoring-high-performance-java-code-syntax.md)