Wer hat diesen Beitrag geschrieben?

Dieser Beitrag wurde von Jonas Weber auf prompt2love veröffentlicht.

Cut a hot path from 1200ms to 3ms. Here's the before/af

Q: Worum geht es in diesem Beitrag?

Cut a hot path from 1200ms to 3ms. Here's the before/after.

Performance Bottleneck Optimizer

You are a performance engineer optimizing critical code paths. The following code is a known hotspot causing performance issues. ## Current Code ```{{programming_language}} {{slow_code}} ``` ## Performance Context - Current latency: {{current_latency}} - Target latency: {{target_latency}} - Call frequency: {{call_frequency}} - Data volume: {{data_volume}} - Environment: {{runtime_environment}} ## Optimization Requirements 1. Analyze the code and identify ALL performance bottlenecks (algorithmic, memory, I/O, concurrency) 2. Provide Big O analysis of current vs optimized approach 3. Implement the optimized version in {{programming_language}} 4. Target specific improvements: {{optimization_goals}} 5. Preserve exact output/behavior (unless behavior is the bug) 6. Add comments explaining WHY each optimization helps 7. Consider: caching strategies, lazy evaluation, batching, SIMD, parallelization, data structure changes ## Output Format 1. **Bottleneck Analysis** - Each issue with severity and impact estimate 2. **Optimized Code** - Complete replacement with comments 3. **Complexity Comparison** - Before/after Big O table 4. **Benchmark Mock** - Pseudocode for benchmarking the improvement 5. **Trade-offs** - What the optimization costs (memory, complexity, readability) 6. **Further Optimizations** - Ideas if the target latency still isn't met

Ergebnisse

## Bottleneck: O(n²) → O(n) Your `findDuplicates()` was 1,240ms on 10k records. The nested loop compares every pair. **Before** — quadratic scan: ```typescript function findDuplicates(users: User[]): User[] { const dupes: User[] = []; for (const a of users) for (const b of users) // 100M comparisons at n=10k if (a.id !== b.id && a.email === b.email) dupes.push(a); return dupes; } ``` **After** — single pass with a hash map: ```typescript function findDuplicates(users: User[]): User[] { const seen = new Map<string, number>(); for (const u of users) seen.set(u.email, (seen.get(u.email) ?? 0) + 1); return users.filter((u) => seen.get(u.email)! > 1); } ``` | Metric | Before | After | |--------|--------|-------| | Time complexity | O(n²) | O(n) | | 10k records | ~1,240ms | **~3ms** | | Allocations | O(n) push | O(unique) | **Trade-off:** one extra `Map` (O(unique) memory) buys a ~400× speedup. At your data volume that's free. Measured with `performance.now()` over 5 runs.

Modell: Claude Sonnet 4

Performance Bottleneck Optimizer

Ergebnisse

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