Conference proceeding
Investigating the Impact of Multiple Dependency Structures on Software Defects
2019 IEEE/ACM 41st International Conference on Software Engineering (ICSE), v 2019-, pp 584-595
May 2019
Abstract
Over the past decades, numerous approaches were proposed to help practitioner to predict or locate defective files. These techniques often use syntactic dependency, history co-change relation, or semantic similarity. The problem is that, it remains unclear whether these different dependency relations will present similar accuracy in terms of defect prediction and localization. In this paper, we present our systematic investigation of this question from the perspective of software architecture. Considering files involved in each dependency type as an individual design space, we model such a design space using one DRSpace. We derived 3 DRSpaces for each of the 117 Apache open source projects, with 643,079 revision commits and 101,364 bug reports in total, and calculated their interactions with defective files. The experiment results are surprising: the three dependency types present significantly different architectural views, and their interactions with defective files are also drastically different. Intuitively, they play completely different roles when used for defect prediction/localization. The good news is that the combination of these structures has the potential to improve the accuracy of defect prediction/localization. In summary, our work provides a new perspective regarding to which type(s) of relations should be used for the task of defect prediction/localization. These quantitative and qualitative results also advance our knowledge of the relationship between software quality and architectural views formed using different dependency types.
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Details
- Title
- Investigating the Impact of Multiple Dependency Structures on Software Defects
- Creators
- Di Cui - Xi'an Jiaotong UniversityTing Liu - Xi'an Jiaotong UniversityYuanfang Cai - Drexel UniversityQinghua Zheng - Xi'an Jiaotong UniversityQiong Feng - Drexel UniversityWuxia Jin - Xi'an Jiaotong UniversityJiaqi Guo - Xi'an Jiaotong UniversityYu Qu - Xi'an Jiaotong University
- Publication Details
- 2019 IEEE/ACM 41st International Conference on Software Engineering (ICSE), v 2019-, pp 584-595
- Publisher
- IEEE
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Computer Science
- Web of Science ID
- WOS:000560373200051
- Scopus ID
- 2-s2.0-85072288728
- Other Identifier
- 991019167519904721
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Collaboration types
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Computer Science, Artificial Intelligence
- Computer Science, Software Engineering
- Computer Science, Theory & Methods