Academic Journal
Black-Box Bug Amplification for Multithreaded Software.
| Title: | Black-Box Bug Amplification for Multithreaded Software. |
|---|---|
| Authors: | Weiss, Yeshayahu, Amram, Gal, Elyasaf, Achiya, Farchi, Eitan, Margalit, Oded, Weiss, Gera |
| Source: | Mathematics (2227-7390); Sep2025, Vol. 13 Issue 18, p2921, 42p |
| Subject Terms: | Computer software testing, Software failures, Heuristic, Prediction models, Parallel programs (Computer programs) |
| Abstract: | Bugs, especially those in concurrent systems, are often hard to reproduce because they manifest only under rare conditions. Testers frequently encounter failures that occur only under specific inputs, often at low probability. We propose an approach to systematically amplify the occurrence of such elusive bugs. We treat the system under test as a black-box system and use repeated trial executions to train a predictive model that estimates the probability of a given input configuration triggering a bug. We evaluate this approach on a dataset of 17 representative concurrency bugs spanning diverse categories. Several model-based search techniques are compared against a brute-force random sampling baseline. Our results show that an ensemble stacking classifier can significantly increase bug occurrence rates across nearly all scenarios, often achieving an order-of-magnitude improvement over random sampling. The contributions of this work include the following: (i) a novel formulation of bug amplification as a rare-event classification problem; (ii) an empirical evaluation of multiple techniques for amplifying bug occurrence, demonstrating the effectiveness of model-guided search; and (iii) a practical, non-invasive testing framework that helps practitioners to expose hidden concurrency faults without altering the internal system architecture. [ABSTRACT FROM AUTHOR] |
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| Database: | Complementary Index |
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| Items | – Name: Title Label: Title Group: Ti Data: Black-Box Bug Amplification for Multithreaded Software. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Weiss%2C+Yeshayahu%22">Weiss, Yeshayahu</searchLink><br /><searchLink fieldCode="AR" term="%22Amram%2C+Gal%22">Amram, Gal</searchLink><br /><searchLink fieldCode="AR" term="%22Elyasaf%2C+Achiya%22">Elyasaf, Achiya</searchLink><br /><searchLink fieldCode="AR" term="%22Farchi%2C+Eitan%22">Farchi, Eitan</searchLink><br /><searchLink fieldCode="AR" term="%22Margalit%2C+Oded%22">Margalit, Oded</searchLink><br /><searchLink fieldCode="AR" term="%22Weiss%2C+Gera%22">Weiss, Gera</searchLink> – Name: TitleSource Label: Source Group: Src Data: Mathematics (2227-7390); Sep2025, Vol. 13 Issue 18, p2921, 42p – Name: Subject Label: Subject Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Computer+software+testing%22">Computer software testing</searchLink><br /><searchLink fieldCode="DE" term="%22Software+failures%22">Software failures</searchLink><br /><searchLink fieldCode="DE" term="%22Heuristic%22">Heuristic</searchLink><br /><searchLink fieldCode="DE" term="%22Prediction+models%22">Prediction models</searchLink><br /><searchLink fieldCode="DE" term="%22Parallel+programs+%28Computer+programs%29%22">Parallel programs (Computer programs)</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Bugs, especially those in concurrent systems, are often hard to reproduce because they manifest only under rare conditions. Testers frequently encounter failures that occur only under specific inputs, often at low probability. We propose an approach to systematically amplify the occurrence of such elusive bugs. We treat the system under test as a black-box system and use repeated trial executions to train a predictive model that estimates the probability of a given input configuration triggering a bug. We evaluate this approach on a dataset of 17 representative concurrency bugs spanning diverse categories. Several model-based search techniques are compared against a brute-force random sampling baseline. Our results show that an ensemble stacking classifier can significantly increase bug occurrence rates across nearly all scenarios, often achieving an order-of-magnitude improvement over random sampling. The contributions of this work include the following: (i) a novel formulation of bug amplification as a rare-event classification problem; (ii) an empirical evaluation of multiple techniques for amplifying bug occurrence, demonstrating the effectiveness of model-guided search; and (iii) a practical, non-invasive testing framework that helps practitioners to expose hidden concurrency faults without altering the internal system architecture. [ABSTRACT FROM AUTHOR] – Name: Abstract Label: Group: Ab Data: <i>Copyright of Mathematics (2227-7390) is the property of MDPI 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: Identifiers: – Type: doi Value: 10.3390/math13182921 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 42 StartPage: 2921 Subjects: – SubjectFull: Computer software testing Type: general – SubjectFull: Software failures Type: general – SubjectFull: Heuristic Type: general – SubjectFull: Prediction models Type: general – SubjectFull: Parallel programs (Computer programs) Type: general Titles: – TitleFull: Black-Box Bug Amplification for Multithreaded Software. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Weiss, Yeshayahu – PersonEntity: Name: NameFull: Amram, Gal – PersonEntity: Name: NameFull: Elyasaf, Achiya – PersonEntity: Name: NameFull: Farchi, Eitan – PersonEntity: Name: NameFull: Margalit, Oded – PersonEntity: Name: NameFull: Weiss, Gera IsPartOfRelationships: – BibEntity: Dates: – D: 15 M: 09 Text: Sep2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 22277390 Numbering: – Type: volume Value: 13 – Type: issue Value: 18 Titles: – TitleFull: Mathematics (2227-7390) Type: main |
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