Using Pattern Position Distribution for Software Failure Detection
- 10.1080/18756891.2013.768442How to use a DOI?
- Sequential Patterns, Classification Algorithm, Software Failure, Anomaly Detection
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.
- © 2017, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - JOUR AU - Chunping Li AU - Ziniu Chen AU - Hao Du AU - Hui Wang AU - George Wilkie AU - JuanC. Augusto AU - Jun Liu PY - 2013 DA - 2013/03/01 TI - Using Pattern Position Distribution for Software Failure Detection JO - International Journal of Computational Intelligence Systems SP - 234 EP - 243 VL - 6 IS - 2 SN - 1875-6883 UR - https://doi.org/10.1080/18756891.2013.768442 DO - 10.1080/18756891.2013.768442 ID - Li2013 ER -