A Learning-to-Rank Based Fault Localization Approach using Likely Invariants

• المؤلفون الرئيسيون: LE, Tien-Duy B., David LO, LE GOUES, Claire, GRUNSKE, Lars
• التنسيق: text
• اللغة: English
• منشور في: Institutional Knowledge at Singapore Management University 2016
• الموضوعات: Learning to Rank; Program Invariants; Automated Debugging; Software Engineering; Theory and Algorithms
• الوصول للمادة أونلاين: https://ink.library.smu.edu.sg/sis_research/3453; https://ink.library.smu.edu.sg/context/sis_research/article/4454/viewcontent/164___A_Learning_to_Rank_Based_Fault_Localization_Approach_using_Likely_Invariants__ISSTA2016_.pdf
• المؤسسة: Singapore Management University

Debugging is a costly process that consumes much of developer time and energy. To help reduce debugging effort, many studies have proposed various fault localization approaches. These approaches take as input a set of test cases (some failing, some passing) and produce a ranked list of program eleme...