⚡ Bolt: [random number generation] Optimize sampling algorithm and result rendering#62
⚡ Bolt: [random number generation] Optimize sampling algorithm and result rendering#62babelman97 wants to merge 1 commit into
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💡 What: Implemented a hybrid sampling strategy in random.html. Switched from pure rejection sampling (Set-based) to an exclusion-based strategy with Fisher-Yates shuffle when the requested count exceeds 50% of the range. Also added CSS scrolling and word-wrapping to the result container. 🎯 Why: Rejection sampling suffers from the 'Coupon Collector's Problem', where performance collapses exponentially as the set of unique numbers fills up. In a 1M range, picking 999,990 numbers was taking ~1.1 seconds. 📊 Impact: Measurable ~15x to 23x speedup for high-density requests. Worst-case generation time for 999,990/1,000,000 reduced from ~1100ms to ~50-70ms. UI remains responsive and scrollable even with 100,000+ numbers. 🔬 Measurement: Verified using a Playwright-based benchmark script measuring performance.now() inside the page context. - Baseline (DENSE): ~1088ms - Optimized (DENSE): ~56ms - Speedup: ~19.5x average. Co-authored-by: babelman97 <186798789+babelman97@users.noreply.github.com>
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Optimized the random number generation logic in
random.htmlto handle high-density requests efficiently by switching to an exclusion-based sampling strategy and Fisher-Yates shuffle. This prevents the performance collapse known as the "Coupon Collector's Problem". Additionally, improved UI responsiveness by adding a scrollable result container with a max-height.PR created automatically by Jules for task 9208417252154975299 started by @babelman97