Two-Level Information-Retrieval-Based Model for Bug Localization Based on Bug Reports
Software bugs are a noteworthy concern for developers and maintainers. When a failure is detected late, it costs more to be fixed. To repair the bug that caused the software failure, the location of the bug must first be known. The process of finding the defective source code elements that led to th...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-01-01
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| Series: | Electronics |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2079-9292/13/2/321 |
| _version_ | 1797344194881126400 |
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| author | Shatha Alsaedi Ahmed A. A. Gad-Elrab Amin Noaman Fathy Eassa |
| author_facet | Shatha Alsaedi Ahmed A. A. Gad-Elrab Amin Noaman Fathy Eassa |
| author_sort | Shatha Alsaedi |
| collection | DOAJ |
| description | Software bugs are a noteworthy concern for developers and maintainers. When a failure is detected late, it costs more to be fixed. To repair the bug that caused the software failure, the location of the bug must first be known. The process of finding the defective source code elements that led to the failure of the software is called bug localization. Effective approaches for automatically locating bugs using bug reports are highly desirable, as they would reduce bug-fixing time, consequently lowering software maintenance costs. With the increasing size and complexity of software projects, manual bug localization methods have become complex, challenging, and time-consuming tasks, which motivates research on automated bug localization techniques. This paper introduces a novel bug localization model, which works on two levels. The first level localizes the buggy classes using an information retrieval approach and it has two additional sub-phases, namely the class-level feature scoring phase and the class-level final score and ranking phase, which ranks the top buggy classes. The second level localizes the buggy methods inside these classes using an information retrieval approach and it has two sub-phases, which are the method-level feature scoring phase and the method-level final score and ranking phase, which ranks the top buggy methods inside the localized classes. A model is evaluated using an AspectJ dataset, and it can correctly localize and rank more than 350 classes and more than 136 methods. The evaluation results show that the proposed model outperforms several state-of-the-art approaches in terms of the mean reciprocal rank (MRR) metrics and the mean average precision (MAP) in class-level bug localization. |
| first_indexed | 2024-03-08T10:58:51Z |
| format | Article |
| id | doaj.art-11c05e47cbc94167aa3be420d635f7bf |
| institution | Directory Open Access Journal |
| issn | 2079-9292 |
| language | English |
| last_indexed | 2024-03-08T10:58:51Z |
| publishDate | 2024-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Electronics |
| spelling | doaj.art-11c05e47cbc94167aa3be420d635f7bf2024-01-26T16:13:36ZengMDPI AGElectronics2079-92922024-01-0113232110.3390/electronics13020321Two-Level Information-Retrieval-Based Model for Bug Localization Based on Bug ReportsShatha Alsaedi0Ahmed A. A. Gad-Elrab1Amin Noaman2Fathy Eassa3Department of Computer Science, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah 21589, Saudi ArabiaDepartment of Computer Science, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah 21589, Saudi ArabiaDepartment of Computer Science, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah 21589, Saudi ArabiaDepartment of Computer Science, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah 21589, Saudi ArabiaSoftware bugs are a noteworthy concern for developers and maintainers. When a failure is detected late, it costs more to be fixed. To repair the bug that caused the software failure, the location of the bug must first be known. The process of finding the defective source code elements that led to the failure of the software is called bug localization. Effective approaches for automatically locating bugs using bug reports are highly desirable, as they would reduce bug-fixing time, consequently lowering software maintenance costs. With the increasing size and complexity of software projects, manual bug localization methods have become complex, challenging, and time-consuming tasks, which motivates research on automated bug localization techniques. This paper introduces a novel bug localization model, which works on two levels. The first level localizes the buggy classes using an information retrieval approach and it has two additional sub-phases, namely the class-level feature scoring phase and the class-level final score and ranking phase, which ranks the top buggy classes. The second level localizes the buggy methods inside these classes using an information retrieval approach and it has two sub-phases, which are the method-level feature scoring phase and the method-level final score and ranking phase, which ranks the top buggy methods inside the localized classes. A model is evaluated using an AspectJ dataset, and it can correctly localize and rank more than 350 classes and more than 136 methods. The evaluation results show that the proposed model outperforms several state-of-the-art approaches in terms of the mean reciprocal rank (MRR) metrics and the mean average precision (MAP) in class-level bug localization.https://www.mdpi.com/2079-9292/13/2/321fault localizationsoftware maintenanceinformation retrievalclass localizationmethod localization |
| spellingShingle | Shatha Alsaedi Ahmed A. A. Gad-Elrab Amin Noaman Fathy Eassa Two-Level Information-Retrieval-Based Model for Bug Localization Based on Bug Reports Electronics fault localization software maintenance information retrieval class localization method localization |
| title | Two-Level Information-Retrieval-Based Model for Bug Localization Based on Bug Reports |
| title_full | Two-Level Information-Retrieval-Based Model for Bug Localization Based on Bug Reports |
| title_fullStr | Two-Level Information-Retrieval-Based Model for Bug Localization Based on Bug Reports |
| title_full_unstemmed | Two-Level Information-Retrieval-Based Model for Bug Localization Based on Bug Reports |
| title_short | Two-Level Information-Retrieval-Based Model for Bug Localization Based on Bug Reports |
| title_sort | two level information retrieval based model for bug localization based on bug reports |
| topic | fault localization software maintenance information retrieval class localization method localization |
| url | https://www.mdpi.com/2079-9292/13/2/321 |
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