SQL Database Design For Developers at php[tek] 2024
Detecting Bug Duplicate Reports Through Locality of Reference
1. Detecting Bug Duplicate Reports Through Locality of Reference Tomi Prifti, Sean Banerjee, Bojan Cukic Lane Department of CSEE West Virginia University Morgantown, WV, USA September 2011
18. Result Comparisons Group Approach Results Hiew, et-al Text analysis Recall rate ~50% Cubranic, et-al Bayesian learning Text categorization Correctly predicted ~30% duplicates Jalbert, et-al Text Similarity Clustering Recall rate ~51% List size 20 Wang, et-al NLP Execution Information 67-93% detection rate (43-72% with NLP) Wang, et-al Enhanced version of prior algorithm 17-31% improvement over state of art Our approach Time Window/Centroids ~53% recall rate