Using Pattern Position Distribution for Software Failure Detection

Chunping Li, Ziniu Chen, Hao Du, Hui Wang, George Wilkie, Juan Carlos Augusto, Jun Liu

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)


We present a novel approach for using the pattern position distribution as features to detect software failure. In this approach, we divide an execution sequence into several sections and compute the pattern distribution in each section. The distribution of all patterns is then used as features to train a classifier. This approach outperforms conventional frequency based methods by more effectively identifying software failures occurring through misused software patterns. Comparative experiments show the effectiveness of our approach.
Original languageEnglish
Pages (from-to)234-243
JournalInternational Journal of Computational Intelligence Systems
Issue number2
Publication statusPublished (in print/issue) - 1 Mar 2013


  • Sequential Patterns
  • Classification Algorithm
  • Software Failure
  • Anomaly Detection


Dive into the research topics of 'Using Pattern Position Distribution for Software Failure Detection'. Together they form a unique fingerprint.

Cite this