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Empirical Investigations of More Practical Fault Localization Approaches

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dc.contributor.authorDao, Tung Manhen
dc.contributor.committeechairMeng, Naen
dc.contributor.committeememberWang, Xiaoyinen
dc.contributor.committeememberChung, Taejoong Tijayen
dc.contributor.committeememberGulzar, Muhammad Alien
dc.contributor.committeememberJi, Boen
dc.contributor.departmentComputer Science and Applicationsen
dc.date.accessioned2023-10-19T08:00:52Zen
dc.date.available2023-10-19T08:00:52Zen
dc.date.issued2023-10-18en
dc.description.abstractDevelopers often spend much of their valuable development time on software debugging and bug finding. In addition, software defects cost software industry as a whole hundreds or even a trillion of US dollars. As a result, many fault localization (FL) techniques for localizing bugs automatically, have been proposed. Despite its popularity, adopting FL in industrial environments has been impractical due to its undesirable accuracy and high runtime overhead cost. Motivated by the real-world challenges of FL applicability, this dissertation addresses these issues by proposing two main enhancements to the existing FL. First, it explores different strategies to combine a variety of program execution information with Information Retrieval-based fault localization (IRFL) techniques to increase FL's accuracy. Second, this dissertation research invents and experiments with the unconventional techniques of Instant Fault Localization (IFL) using the innovative concept of triggering modes. Our empirical evaluations of the proposed approaches on various types of bugs in a real software development environment shows that both FL's accuracy is increased and runtime is reduced significantly. We find that execution information helps increase IRFL's Top-10 by 17–33% at the class level, and 62–100% at the method level. Another finding is that IFL achieves as much as 100% runtime cost reduction while gaining comparable or better accuracy. For example, on single-location bugs, IFL scores 73% MAP, compared with 56% of the conventional approach. For multi-location bugs, IFL's Top-1 performance on real bugs is 22%, just right below 24% that of the existing FL approaches. We hope the results and findings from this dissertation help make the adaptation of FL in the real-world industry more practical and prevalent.en
dc.description.abstractgeneralIn software engineering, fault localization (FL) is a popular technique to automatically find software bugs, which cost a huge loss of hundreds of billions of US dollars on the software industry. Despite its high demanding and popularity, adopting FL in industrial software companies remains impractical. To help resolve this applicability problem, this dissertation proposed enhanced techniques to localize bugs more accurately and with less overhead runtime expenses. As a result, FL becomes more practical and efficient for software companies.en
dc.description.degreeDoctor of Philosophyen
dc.format.mediumETDen
dc.identifier.othervt_gsexam:38673en
dc.identifier.urihttp://hdl.handle.net/10919/116510en
dc.language.isoenen
dc.publisherVirginia Techen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectSoftware Engineeringen
dc.subjectTestingen
dc.subjectDebuggingen
dc.subjectFault Localizationen
dc.subjectSpectrum-baseden
dc.subjectInformation Retrievalen
dc.subjectSlicingen
dc.subjectCoverageen
dc.subjectExecution Informationen
dc.subjectAbstract State Machineen
dc.subjectCloud Computingen
dc.titleEmpirical Investigations of More Practical Fault Localization Approachesen
dc.typeDissertationen
thesis.degree.disciplineComputer Science and Applicationsen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.leveldoctoralen
thesis.degree.nameDoctor of Philosophyen

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