SLIM: a Scalable and Interpretable Light-weight Fault Localization Algorithm for Imbalanced Data in Microservice

• Published in: IEEE/ACM International Conference on Automated Software Engineering : [proceedings] pp. 27 - 39
• Main Authors: Ren, Rui, Yang, Jingbang, Yang, Linxiao, Gu, Xinyue, Sun, Liang
• Format: Conference Proceeding
• Language: English
• Published: ACM 27.10.2024
• Subjects: Classification algorithms; Debugging; Imbalanced Classification; Interpretability; Location awareness; Microserivce Fault Localization; Microservice architectures; Minorize-Maximization; Reliability engineering; Software; Software algorithms; Software engineering; Software reliability; Submodular Optimization; Training
• ISSN: 2643-1572
• DOI: 10.1145/3691620.3694984

In real-world microservice systems, the newly deployed service -one kind of change service, could lead to a new type of minority fault. Existing state-of-the-art (SOTA) methods for fault localization rarely consider the imbalanced fault classification in change service. This paper proposes a novel m...