⚡ Bolt: optimize random number generation for high density#57
⚡ Bolt: optimize random number generation for high density#57babelman97 wants to merge 1 commit into
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Optimized the random number generator in random.html by implementing a hybrid sampling strategy. For high-density requests (>50% of range), the generator now uses exclusion-based sampling paired with a Fisher-Yates shuffle. This prevents the performance collapse associated with the 'Coupon Collector's Problem' in the original rejection sampling logic. Measured impact: ~7.8x speedup (approx. 2119ms to 269ms) for 999,990 unique numbers in a 1,000,000 range. Co-authored-by: babelman97 <186798789+babelman97@users.noreply.github.com>
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💡 What: Implemented a hybrid sampling strategy in `random.html`. Added a Fisher-Yates shuffle helper and conditional logic to switch between rejection sampling (for sparse requests) and exclusion sampling (for dense requests).
🎯 Why: The original implementation used rejection sampling exclusively. As the requested count approaches the total range size, the probability of generating a new unique number drops significantly, causing the loop to run millions of redundant iterations.
📊 Impact: Reduces execution time by ~87% for high-density requests (e.g., 999,990 numbers in a 1,000,000 range), improving performance from ~2.1s to ~0.27s.
🔬 Measurement: Benchmarked using Playwright by executing `generateRandomNumbers()` within a browser page evaluate block and measuring the delta via `performance.now()`. Verified functional correctness (uniqueness, count, range) for all sampling paths.
PR created automatically by Jules for task 11560059252563854543 started by @babelman97