Poster: Identification of Methods with Low Fault Risk
Abstract
Test resources are usually limited and therefore it is often not possible to completely test an application before a release. Therefore, testers need to focus their activities on the relevant code regions. In this paper, we introduce an inverse defect prediction approach to identify methods that contain hardly any faults. We applied our approach to six Java open-source projects and show that on average 31.6% of the methods of a project have a low fault risk; they contain in total, on average, only 5.8% of all faults. Furthermore, the results suggest that, unlike defect prediction, our approach can also be applied in cross-project prediction scenarios. Therefore, inverse defect prediction can help prioritize untested code areas and guide testers to increase the fault detection probability.
Keywords
Cite
@article{arxiv.1805.01132,
title = {Poster: Identification of Methods with Low Fault Risk},
author = {Rainer Niedermayr and Tobias Röhm and Stefan Wagner},
journal= {arXiv preprint arXiv:1805.01132},
year = {2018}
}
Comments
ICSE 2018 Poster Track