Automated support for classifying software failure reports
Andy Podgurski, David Leon, Patrick Francis, Wes Masri, Melinda Minch · 2003
This paper proposes automated support for classi ying reported software failures in order to facilitate prioritizing them and diagnosing their causes. A classification strategy is presented that involves the use of supervised and unsupervised pattern classification and multivariate visualization. These techniques are applied to profiles o f failed executions in order to group together failures with the same or similar causes. The resulting classification is then used to assess the frequency and severity o f failures caused by particular defects and to help diagnose those defects. The results of applying the proposed classification strategy to failures of three large subject programs are reported. that the strategy can be effective. These results indicate