TY - JOUR
T1 - A Formal Explainer for Just-In-Time Defect Predictions
AU - Yu, Jinqiang
AU - Fu, Michael
AU - Ignatiev, Alexey
AU - Tantithamthavorn, Chakkrit
AU - Stuckey, Peter
N1 - Publisher Copyright:
© 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.
PY - 2024/8/26
Y1 - 2024/8/26
N2 - Just-in-Tim e (JIT) defect prediction has been proposed to help teams prioritize the limited resources on the most risky commits (or pull requests), yet it remains largely a black box, whose predictions are not explainable or actionable to practitioners. Thus, prior studies have applied various model-agnostic techniques to explain the predictions of JIT models. Yet, explanations generated from existing model-agnostic techniques are still not formally sound, robust, and actionable. In this article, we propose FoX, a Formal eXplainer for JIT Defect Prediction, which builds on formal reasoning about the behavior of JIT defect prediction models and hence is able to provide provably correct explanations, which are additionally guaranteed to be minimal. Our experimental results show that FoX is able to efficiently generate provably correct, robust, and actionable explanations, while existing model-agnostic techniques cannot. Our survey study with 54 software practitioners provides valuable insights into the usefulness and trustworthiness of our FoX approach; 86% of participants agreed that our approach is useful, while 74% of participants found it trustworthy. Thus, this article serves as an important stepping stone towards trustable explanations for JIT models to help domain experts and practitioners better understand why a commit is predicted as defective and what to do to mitigate the risk.
AB - Just-in-Tim e (JIT) defect prediction has been proposed to help teams prioritize the limited resources on the most risky commits (or pull requests), yet it remains largely a black box, whose predictions are not explainable or actionable to practitioners. Thus, prior studies have applied various model-agnostic techniques to explain the predictions of JIT models. Yet, explanations generated from existing model-agnostic techniques are still not formally sound, robust, and actionable. In this article, we propose FoX, a Formal eXplainer for JIT Defect Prediction, which builds on formal reasoning about the behavior of JIT defect prediction models and hence is able to provide provably correct explanations, which are additionally guaranteed to be minimal. Our experimental results show that FoX is able to efficiently generate provably correct, robust, and actionable explanations, while existing model-agnostic techniques cannot. Our survey study with 54 software practitioners provides valuable insights into the usefulness and trustworthiness of our FoX approach; 86% of participants agreed that our approach is useful, while 74% of participants found it trustworthy. Thus, this article serves as an important stepping stone towards trustable explanations for JIT models to help domain experts and practitioners better understand why a commit is predicted as defective and what to do to mitigate the risk.
KW - Explainable AI for SE
KW - Just-In-Time Defect Prediction
KW - Formal Explainability
KW - Software Quality
UR - http://www.scopus.com/inward/record.url?scp=85212830966&partnerID=8YFLogxK
U2 - 10.1145/3664809
DO - 10.1145/3664809
M3 - Article
AN - SCOPUS:85212830966
SN - 1049-331X
VL - 33
JO - ACM Transactions on Software Engineering and Methodology
JF - ACM Transactions on Software Engineering and Methodology
IS - 7
M1 - 187
ER -