Projects per year
Abstract
Software defect prediction models are classifiers that are constructed from historical software data. Such software defect prediction models have been proposed to help developers optimize the limited Software Quality Assurance (SQA) resources and help managers develop SQA plans. Prior studies have different goals for their defect prediction models and use different techniques for generating visual explanations of their models. Yet, it is unclear what are the practitioners' perceptions of (1) these defect prediction model goals, and (2) the model-agnostic techniques used to visualize these models. We conducted a qualitative survey to investigate practitioners' perceptions of the goals of defect prediction models and the model-agnostic techniques used to generate visual explanations of defect prediction models. We found that (1) 82%-84% of the respondents perceived that the three goals of defect prediction models are useful; (2) LIME is the most preferred technique for understanding the most important characteristics that contributed to a prediction of a file, while ANOVA/VarImp is the second most preferred technique for understanding the characteristics that are associated with software defects in the past. Our findings highlight the significance of investigating how to improve the understanding of defect prediction models and their predictions. Hence, model-agnostic techniques from explainable AI domain may help practitioners to understand defect prediction models and their predictions.
Original language | English |
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Title of host publication | Proceedings - 2021 IEEE/ACM 18th International Conference on Mining Software Repositories, MSR 2021 |
Editors | Kelly Blincoe, Meiyappan Nagappan |
Place of Publication | Piscataway NJ USA |
Publisher | IEEE, Institute of Electrical and Electronics Engineers |
Pages | 432-443 |
Number of pages | 12 |
ISBN (Electronic) | 9781728187105 |
ISBN (Print) | 9781665429856 |
DOIs | |
Publication status | Published - 2021 |
Event | IEEE International Working Conference on Mining Software Repositories 2021 - Online, Madrid, Spain Duration: 22 May 2021 → 30 May 2021 Conference number: 18th https://ieeexplore-ieee-org.ezproxy.lib.monash.edu.au/xpl/conhome/9463061/proceeding (Proceedings) |
Publication series
Name | Proceedings - 2021 IEEE/ACM 18th International Conference on Mining Software Repositories, MSR 2021 |
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Publisher | IEEE, Institute of Electrical and Electronics Engineers |
ISSN (Print) | 2574-3848 |
ISSN (Electronic) | 2574-3864 |
Conference
Conference | IEEE International Working Conference on Mining Software Repositories 2021 |
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Abbreviated title | MSR 2021 |
Country/Territory | Spain |
City | Madrid |
Period | 22/05/21 → 30/05/21 |
Internet address |
Keywords
- Defect Prediction
- Explainable AI
- Software Analytics
- Software Quality Assurance
Projects
- 2 Finished
-
Practical and Explainable Analytics to Prevent Future Software Defects
Australian Research Council (ARC)
2/03/20 → 2/03/23
Project: Research
-
HCMDSE: Human-centric Model-driven Software Engineering
Australian Research Council (ARC)
3/02/20 → 2/02/25
Project: Research