⚡ Bolt: Optimize unique random sampling in random.html#108
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- Implement hybrid sampling approach: Rejection Sampling (Set) for low density (<50%) and Sparse Fisher-Yates (Map) for high density (>=50%). - Fix O(N^2) performance bottleneck when generating many unique numbers. - Improve high-density generation time from ~1160ms to ~416ms (avg for 990k numbers in 1M range). - Fix validation bug allowing single-value ranges (min == max). - Add scrollable container for large result sets to maintain UI responsiveness. - Use textContent for faster DOM updates. Co-authored-by: babelman97 <[email protected]>
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💡 What:
Optimized the unique random number generation in
random.htmlby replacing the simple rejection sampling approach with a hybrid method. It now uses a Sparse Fisher-Yates algorithm for high-density requests (where collisions are frequent) and maintains the memory-efficientSetapproach for low-density requests.🎯 Why:
The previous implementation used a
Setand kept generating numbers until it reached the desired count. As the number of requested values approached the total range size, collisions became extremely frequent, causing the performance to degrade significantly (approaching O(N^2) in the worst case).📊 Impact:
minValue >= maxValuecheck erroneously blocked valid single-value ranges (e.g., generating 1 number from [5, 5]).max-heightandoverflow-y: autoto the results container to prevent the page from growing indefinitely and becoming unresponsive when displaying hundreds of thousands of numbers.🔬 Measurement:
Measured using
performance.now()in a browser-like environment and verified with Node.js benchmarks. Visual verification performed via Playwright to ensure the UI handles both small and large result sets correctly.PR created automatically by Jules for task 4782530439998961536 started by @babelman97