CASTR: A Web-based Tool for Creating Bug Report Assignment Recommenders
dc.contributor.author | Devaiya, Disha Thakarshibhai | |
dc.contributor.author | University of Lethbridge. Faculty of Arts and Science | |
dc.contributor.supervisor | Anvik, John | |
dc.date.accessioned | 2019-08-27T17:49:21Z | |
dc.date.available | 2019-08-27T17:49:21Z | |
dc.date.issued | 2019 | |
dc.degree.level | Masters | en_US |
dc.description.abstract | Large software development projects receive a large number of bug reports every day. Bug triage is a process where issues are screened and prioritized. Bug triage takes significant time and resources. For reducing the workload of project members, researchers have proposed using assignment recommenders. As the creation of bug report assignment recommenders is complex, we propose a web-based tool called the Creation Assistant for Supporting Triage Recommenders (CASTR) to assist the project members with the creation of assignment recommenders. CASTR assists a user in labeling and filtering the bug reports used for creating a project-specific assignment recommender. As the field study results present, recommenders can be created with good accuracy using CASTR such as 50-95% for Top-1 recommendations, 20-80% for Top-3 recommendations and 10-70% for Top-5 recommendations. Most participants (60%) found CASTR easy to use and were very likely to recommend CASTR for creating an assignment recommender. | en_US |
dc.description.sponsorship | Natural Sciences and Engineering Research Council (NSERC) | en_US |
dc.identifier.uri | https://hdl.handle.net/10133/5520 | |
dc.language.iso | en_US | en_US |
dc.proquest.subject | Computer science [0984] | en_US |
dc.proquest.subject | Computer engineering [0464] | en_US |
dc.proquestyes | Yes | en_US |
dc.publisher | Lethbridge, Alta. : University of Lethbridge, Dept. of Mathematics and Computer Science | en_US |
dc.publisher.department | Department of Mathematics and Computer Science | en_US |
dc.publisher.faculty | Arts and Science | en_US |
dc.relation.ispartofseries | Thesis (University of Lethbridge. Faculty of Arts and Science) | en_US |
dc.subject | Computer bugs | en_US |
dc.subject | Computer software Development | en_US |
dc.subject | Machine learning | en_US |
dc.subject | Recommender systems (Information filtering) | en_US |
dc.title | CASTR: A Web-based Tool for Creating Bug Report Assignment Recommenders | en_US |
dc.type | Thesis | en_US |