Λεπτομέρειες βιβλιογραφικής εγγραφής
| Τίτλος: |
MMFL: Multi-modal software fault localizer using structural source code features. |
| Συγγραφείς: |
Barik, Paramananda, Kishore, Pushkar, Mohapatra, Durga Prasad, Nayak, Gayatri |
| Πηγή: |
AIP Conference Proceedings; 2026, Vol. 3388 Issue 1, p1-9, 9p |
| Θεματικοί όροι: |
Artificial neural networks, Debugging, Defect tracking (Computer software development) |
| Περίληψη: |
Software failures in applications result in significant costs for organizations, making it essential to identify and fix defects efficiently. Software fault localization, i.e., the process of pinpointing the location of bugs, helps developers reduce debugging and maintenance efforts. Automated fault localization further accelerates bug finding and patching. Recent studies leverage artificial neural networks (ANNs) for fault localization, typically using binary branches and func-tions coverage data to train the models. However, the proposed approach enhances the performance of fault localizer by considering the number of times each branch and function are covered. The Siemens suite is employed for experiments and evaluations. A key finding of this research is that the equal (50%) split of training and testing data contributes to the higher model performance instead of 7:3 and 8:2 split. It is mainly due to presence of similar training samples in the training set leading to overfitting of the trained model. After testing, the proposed MMFL model successfully identifies all bugs in every program version, requiring just 16% of the code lines to be scanned, which is significantly less than the amount needed by current state-of-the-art methods. [ABSTRACT FROM AUTHOR] |
|
Copyright of AIP Conference Proceedings is the property of American Institute of Physics and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) |
| Βάση Δεδομένων: |
Complementary Index |