Effective Lightweight Software Fault Localization Combined with Fault Context and Test Suite Optimization.
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| Title: | Effective Lightweight Software Fault Localization Combined with Fault Context and Test Suite Optimization. |
|---|---|
| Authors: | Saxena, Amol1 amolsaxena2015@gmail.com, Bhatnagar, Roheet2 roheet.bhatnagar@jaipur.manipal.edu, Srivastava, Devesh Kumar3 devesh988@yahoo.com |
| Source: | Engineering Letters. Apr2024, Vol. 32 Issue 4, p835-870. 36p. |
| Subjects: | Siemens AG, Software localization, Evidence gaps, Debugging, Computer software testing, Statistics, Scalability, Test methods |
| Abstract: | Locating software faults during debugging is crucial yet challenging. Automated techniques, such as spectrum-based fault localization (SBFL), aid developers in efficiently localizing faults by analyzing program execution information and utilizing statistical approaches to rank program entities according to their suspiciousness. SBFL is also known as lightweight fault localization because of its scalability and minimal computational overhead. While essential, there has been limited research on how test suites affect fault localization. In this paper, we show how test suites impact fault localization and how they can be optimized for better results. SBFL techniques have some inherent limitations, especially in diagnosing faults within loop bodies or iteration statements. Additionally, identical suspiciousness levels can result in ties. While SBFL techniques effectively rank faulty program entities among the Top-N suspicious entities, they might not consistently position the faulty entity within the initial few positions. To address these research gaps, this paper proposes a hybrid approach that combines test suite optimization, statement execution frequency, and fault context concepts to enhance the performance of existing SBFL techniques in single fault scenarios. We evaluate our approach using three popular SBFL methods (Ochiai, Jaccard, and DStar) on Siemens benchmarks and four large real-world programs (flex, grep, sed, and space) with their test suites. The results demonstrate a significant enhancement in fault localization performance when applying our proposed approach to existing SBFL methods. For example, when applied to Ochiai, it reduces examined statements by 62.76% and 65.23% on average for the two test suites, respectively. Furthermore, it identifies 52% of faults by examining only 1% or less of the code and locates 60% of faults by analyzing only 0.1% or less of the code in Siemens and four large real-world programs, respectively. Similar improvements are observed when our approach is applied to Jaccard and DStar methods on the same test suites. We also show that our results are statistically significant, validating that our approach substantially improves the performance of existing SBFL techniques. [ABSTRACT FROM AUTHOR] |
| Copyright of Engineering Letters is the property of International Association of Engineers (IAENG) 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.) | |
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| Items | – Name: Title Label: Title Group: Ti Data: Effective Lightweight Software Fault Localization Combined with Fault Context and Test Suite Optimization. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Saxena%2C+Amol%22">Saxena, Amol</searchLink><relatesTo>1</relatesTo><i> amolsaxena2015@gmail.com</i><br /><searchLink fieldCode="AR" term="%22Bhatnagar%2C+Roheet%22">Bhatnagar, Roheet</searchLink><relatesTo>2</relatesTo><i> roheet.bhatnagar@jaipur.manipal.edu</i><br /><searchLink fieldCode="AR" term="%22Srivastava%2C+Devesh+Kumar%22">Srivastava, Devesh Kumar</searchLink><relatesTo>3</relatesTo><i> devesh988@yahoo.com</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Engineering+Letters%22">Engineering Letters</searchLink>. Apr2024, Vol. 32 Issue 4, p835-870. 36p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Siemens+AG%22">Siemens AG</searchLink><br /><searchLink fieldCode="DE" term="%22Software+localization%22">Software localization</searchLink><br /><searchLink fieldCode="DE" term="%22Evidence+gaps%22">Evidence gaps</searchLink><br /><searchLink fieldCode="DE" term="%22Debugging%22">Debugging</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+software+testing%22">Computer software testing</searchLink><br /><searchLink fieldCode="DE" term="%22Statistics%22">Statistics</searchLink><br /><searchLink fieldCode="DE" term="%22Scalability%22">Scalability</searchLink><br /><searchLink fieldCode="DE" term="%22Test+methods%22">Test methods</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Locating software faults during debugging is crucial yet challenging. Automated techniques, such as spectrum-based fault localization (SBFL), aid developers in efficiently localizing faults by analyzing program execution information and utilizing statistical approaches to rank program entities according to their suspiciousness. SBFL is also known as lightweight fault localization because of its scalability and minimal computational overhead. While essential, there has been limited research on how test suites affect fault localization. In this paper, we show how test suites impact fault localization and how they can be optimized for better results. SBFL techniques have some inherent limitations, especially in diagnosing faults within loop bodies or iteration statements. Additionally, identical suspiciousness levels can result in ties. While SBFL techniques effectively rank faulty program entities among the Top-N suspicious entities, they might not consistently position the faulty entity within the initial few positions. To address these research gaps, this paper proposes a hybrid approach that combines test suite optimization, statement execution frequency, and fault context concepts to enhance the performance of existing SBFL techniques in single fault scenarios. We evaluate our approach using three popular SBFL methods (Ochiai, Jaccard, and DStar) on Siemens benchmarks and four large real-world programs (flex, grep, sed, and space) with their test suites. The results demonstrate a significant enhancement in fault localization performance when applying our proposed approach to existing SBFL methods. For example, when applied to Ochiai, it reduces examined statements by 62.76% and 65.23% on average for the two test suites, respectively. Furthermore, it identifies 52% of faults by examining only 1% or less of the code and locates 60% of faults by analyzing only 0.1% or less of the code in Siemens and four large real-world programs, respectively. Similar improvements are observed when our approach is applied to Jaccard and DStar methods on the same test suites. We also show that our results are statistically significant, validating that our approach substantially improves the performance of existing SBFL techniques. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Engineering Letters is the property of International Association of Engineers (IAENG) 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.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 36 StartPage: 835 Subjects: – SubjectFull: Siemens AG Type: general – SubjectFull: Software localization Type: general – SubjectFull: Evidence gaps Type: general – SubjectFull: Debugging Type: general – SubjectFull: Computer software testing Type: general – SubjectFull: Statistics Type: general – SubjectFull: Scalability Type: general – SubjectFull: Test methods Type: general Titles: – TitleFull: Effective Lightweight Software Fault Localization Combined with Fault Context and Test Suite Optimization. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Saxena, Amol – PersonEntity: Name: NameFull: Bhatnagar, Roheet – PersonEntity: Name: NameFull: Srivastava, Devesh Kumar IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 04 Text: Apr2024 Type: published Y: 2024 Identifiers: – Type: issn-print Value: 1816093X Numbering: – Type: volume Value: 32 – Type: issue Value: 4 Titles: – TitleFull: Engineering Letters Type: main |
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