⚡ Optimize game profile lookup in LocalGameDetection - #27
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This commit improves the performance of the game detection logic in the Lira Companion. The original implementation used nested loops resulting in O(N*M*P) complexity. The new implementation uses an inverted index (Map) for process-to-game lookups and a Set for running processes, achieving O(P + G) complexity while maintaining the original profile priority. Performance Impact: - Baseline (Original): ~5.5s for 10,000 iterations (106 profiles, 500 processes) - Optimized: ~2.6s for 10,000 iterations (including process list parsing) - Net improvement: ~2.1x faster at scale. Co-authored-by: Rukafuu <111822334+Rukafuu@users.noreply.github.com>
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💡 What: The optimization implemented
Optimized the game detection logic in
LocalGameDetectionby:processToGameIdMap) in the constructor to map process names to game IDs in O(1).detectActiveGameto use aSetfor running processes, allowing for O(1) membership checks.gameProfilesin their defined order of priority to select the active game.🎯 Why: The performance problem it solves
The original code performed a nested loop over all game profiles, their associated process names, and then searched the entire list of running processes for each name using
Array.prototype.some(). This resulted in O(N * M * P) complexity, which becomes inefficient as the number of supported games or running processes increases.📊 Measured Improvement
Using a benchmark script with 106 profiles and 500 simulated processes:
Verification tests confirmed that game priority and specialized checks like
requiresWindowCheck(football detection) remain functional and correct.PR created automatically by Jules for task 4097993275673669113 started by @Rukafuu