Enhancing code review for improved code quality with language model-driven approaches

Simple item page
dc.contributor.advisorPrince, Enamul Hoque
dc.contributor.authorRahman, Shadikur
dc.date.accessioned2024-03-18T18:14:09Z
dc.date.available2024-03-18T18:14:09Z
dc.date.issued2024-03-16
dc.date.updated2024-03-16T10:50:06Z
dc.degree.disciplineComputer Science
dc.degree.levelMaster's
dc.degree.nameMSc - Master of Science
dc.description.abstractCode review is essential for maintaining software development standards, yet achieving effective reviews and issue resolution remains challenging. This thesis introduces RefineCode, an application tool to find actionable code reviews and provide similar code reviews as references within an organization, aiding developers in resolving issues effectively. To this end, we collected 9,500 code reviews from five private projects in an industrial setting and empirically evaluated various classification methods for identifying actionable code reviews. RefineCode automatically recommends relevant solutions from Stack Overflow based on textual similarity and entity linking between code reviews and Stack Overflow issues. Additionally, it integrates a chatbot feature, leveraging large language models to propose potential solutions for actionable code reviews. These features empower developers to make informed decisions, enhancing code quality by guiding issue resolution without reinforcing misunderstandings.
dc.identifier.urihttps://hdl.handle.net/10315/41946
dc.languageen
dc.rightsAuthor owns copyright, except where explicitly noted. Please contact the author directly with licensing requests.
dc.subjectComputer science
dc.subjectArtificial intelligence
dc.subjectComputer engineering
dc.subject.keywordsCode review
dc.subject.keywordsReview classification
dc.subject.keywordsFeature extraction
dc.subject.keywordsEntity linking
dc.subject.keywordsRecommendation
dc.subject.keywordsRefinecode chatbot
dc.titleEnhancing code review for improved code quality with language model-driven approaches
dc.typeElectronic Thesis or Dissertation

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Rahman_Shadikur_2024_Masters.pdf
Size:
919.85 KB
Format:
Adobe Portable Document Format
Download
License bundle
Now showing 1 - 2 of 2
No Thumbnail Available
Name:
license.txt
Size:
1.87 KB
Format:
Plain Text
Description:
Download
No Thumbnail Available
Name:
YorkU_ETDlicense.txt
Size:
3.39 KB
Format:
Plain Text
Description:
Download

Collections

Computer Science

All items in the YorkSpace institutional repository are protected by copyright, with all rights reserved except where explicitly noted.