Automatic sentence annotation for more useful bug report summarization

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dc.contributor.authorGalappaththi, Akalanka
dc.contributor.authorUniversity of Lethbridge. Faculty of Arts and Science
dc.contributor.supervisorAnvik, John
dc.date.accessioned2020-09-23T21:09:31Z
dc.date.available2020-09-23T21:09:31Z
dc.date.issued2020
dc.degree.levelMastersen_US
dc.description.abstractBug reports are a useful software artifact with software developers referring to them for various information needs. As bug reports can become long, users of bug reports may need to spend a lot of time reading them. Previous studies developed summarizers and the quality of summaries was determined based on human-created gold-standard summaries. We believe creating such summaries for evaluating summarizers is not a good practice. First, we have observed a high level of disagreement between the annotated summaries. Second, the number of annotators involved is lower than the established minimum for the creation of a stable annotated summary. Finally, the traditional fixed threshold of 25% of the bug report word count does not adequately serve the different information needs. Consequently, we developed an automatic sentence annotation method to identify content in bug report comments which allows bug report users to customize a view for their task-dependent information needs.en_US
dc.identifier.urihttps://hdl.handle.net/10133/5770
dc.language.isoenen_US
dc.proquest.subject0984en_US
dc.proquestyesYesen_US
dc.publisherLethbridge, Alta. : University of Lethbridge, Department of Mathematics and Computer Scienceen_US
dc.publisher.departmentDepartment of Mathematics and Computer Scienceen_US
dc.publisher.facultyArts and Scienceen_US
dc.relation.ispartofseriesThesis (University of Lethbridge. Faculty of Arts and Science)en_US
dc.subjectbug reportsen_US
dc.subjectautomatic sentence annotationen_US
dc.subjectannotated summariesen_US
dc.subjectbug report summarizationen_US
dc.subjectsentence labellingen_US
dc.subjectSoftware failures -- Documentation -- Abstractsen_US
dc.subjectNatural language processing (Computer science)en_US
dc.subjectAutomatic abstractingen_US
dc.subjectText processing (Computer science)en_US
dc.subjectAbstracts -- Data processingen_US
dc.subjectDissertations, Academicen_US
dc.titleAutomatic sentence annotation for more useful bug report summarizationen_US
dc.typeThesisen_US
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