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Federated Learning in Software Engineering: A Comprehensive Study on Commit Prediction and Name-based Bug Detection

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dc.contributor.advisorRoy, Banani
dc.contributor.committeeMemberRochan, Mrigank
dc.contributor.committeeMemberDeters, Ralph
dc.creatorIslam, Md Rayhan
dc.creator.orcid0009-0005-0022-2716
dc.date.accessioned2024-01-30T19:42:55Z
dc.date.copyright2024
dc.date.created2024-04
dc.date.issued2024-01-30
dc.date.submittedApril 2024
dc.date.updated2024-01-30T19:42:55Z
dc.description.abstract
This item is under an embargo. Access to the abstract will not be permitted until 2025-01-30
dc.format.mimetypeapplication/pdf
dc.identifier.urihttps://hdl.handle.net/10388/15473
dc.language.isoen
dc.subjectBug Prediction, JIT, Machine Learning, Federated Learning, Deep Learning, Named-Based Bug, Bug Detection
dc.titleFederated Learning in Software Engineering: A Comprehensive Study on Commit Prediction and Name-based Bug Detection
dc.typeThesis
dc.type.materialtext
local.embargo.lift2025-01-30
local.embargo.terms2025-01-30
thesis.degree.departmentComputer Science
thesis.degree.disciplineComputer Science
thesis.degree.grantorUniversity of Saskatchewan
thesis.degree.levelMasters
thesis.degree.nameMaster of Science (M.Sc.)

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