Reranking-based Crash Report Deduplication
Akira Moroo, Akiko Aizawa, Takayuki Hamamoto · Proceedings/Proceedings of the ... International Conference on Software Engineering and Knowledge Engineering · 2017
Software projects collect and deduplicate vastly numerous crash reports from users to fix bugs efficiently.However, most existing automated methods have performance issues during large-scale clustering.We propose a rerankingbased crash report clustering method.Our method is a combination of two earlier methods.By computing similarity used in ReBucket for the crash reports that are highly similar to the query crash report, the method can process reports with throughput equal to that of PartyCrasher.We also introduce an automatically generated dataset for crash report clustering tasks.The evaluation revealed that our method performs at high processing speed while maintaining high accuracy.