Tracking Down Misguiding Terms for Locating Bugs in Deep Learning-Based Software (Student Abstract)
نویسندگان
چکیده
Bugs in source files (SFs) may cause software malfunction, inconveniencing users and even leading to catastrophic accidents. Therefore, the bugs SFs should be found fixed quickly. However, from hundreds of candidate SFs, finding buggy is tedious time consuming. To lessen burden on developers, deep learning-based bug localization (DLBL) tools can utilized. Text terms reports play an important role. some provide incorrect information degrade performance. those are defined here as "misguiding terms," explainable-artificial-intelligence-based identification method proposed. The effectiveness proposed for DLBL was investigated. When misguiding were removed, mean average precision model improved by 33% average.
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ژورنال
عنوان ژورنال: Proceedings of the ... AAAI Conference on Artificial Intelligence
سال: 2022
ISSN: ['2159-5399', '2374-3468']
DOI: https://doi.org/10.1609/aaai.v36i11.21628