⚡ Bolt: [optimize random number generation]#49
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Implemented a hybrid sampling strategy for unique random numbers: - Use rejection sampling (Set) for sparse requests (<50% of range). - Use exclusion-based sampling (partial Fisher-Yates shuffle) for dense requests. This avoids the Coupon Collector's Problem and ensures O(count) performance. Co-authored-by: babelman97 <186798789+babelman97@users.noreply.github.com>
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💡 What: Implemented a hybrid sampling strategy in
random.html'sgenerateRandomNumbersfunction.🎯 Why: The original rejection sampling (using a Set) degrades in performance as the requested count approaches the range size due to the Coupon Collector's Problem (frequent collisions).
📊 Impact: Achieves a ~9x speedup for high-density requests (e.g., requesting 99,000 numbers from a range of 100,000) while remaining memory-efficient for sparse requests.
🔬 Measurement: Verified uniqueness and range correctness via Playwright; benchmarked execution time for high-density scenarios showing significant reduction in execution time for dense requests.
PR created automatically by Jules for task 3331217452926699019 started by @babelman97