XAI4FL: enhancing spectrum-based fault localization with explainable artificial intelligence

XAI4FL: enhancing spectrum-based fault localization with explainable artificial intelligence

Manually finding the program unit (e.g., class, method, or statement) responsible for a fault is tedious and time-consuming. To mitigate this problem, many fault localization techniques have been proposed. A popular family of such techniques is spectrum-based fault localization (SBFL), which takes p...

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Bibliographic Details
Main Authors: RATNADIRA WIDYASARI, PRANA, Gede Artha Azriadi, AGUS HARYONO, Stefanus, TIAN, Yuan, ZACHIARY, Hafil Noer, LO, David
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2022
Subjects:
Fault localization
Explainable artificial intelligence (XAI)
Model-agnostic explanation technique
Spectrum-based fault localization
Testing and debugging
Software Engineering
Online Access:https://ink.library.smu.edu.sg/sis_research/7639
https://ink.library.smu.edu.sg/context/sis_research/article/8642/viewcontent/929800a499.pdf
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Institution: Singapore Management University
Language: English

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https://ink.library.smu.edu.sg/sis_research/7639
https://ink.library.smu.edu.sg/context/sis_research/article/8642/viewcontent/929800a499.pdf

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