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dc.rights.licenseCC-BY-NC-ND
dc.contributor.advisorFarshidi, S.
dc.contributor.authorBeigzadeh, Parsa
dc.date.accessioned2024-03-28T00:02:48Z
dc.date.available2024-03-28T00:02:48Z
dc.date.issued2024
dc.identifier.urihttps://studenttheses.uu.nl/handle/20.500.12932/46213
dc.description.abstractThe choice of software components is a crucial task in software engineering that has a big impact on the output and success of a project. The purpose of this thesis is to investigate the use of knowledge-based recommendation systems for software component selection. In order to identify previous studies and categorize them for the application of knowledge-based approaches in software architecture, the research will entail a systematic mapping study . The thesis aims to investigate the potential and difficulties of software repository mining for software engineering purposes. Specifically, it will examine how to extract software-related knowledge from various platforms . The results of this thesis will contribute to the creation of a knowledge-driven framework that will help software engineers make well-informed deci- sions about the selection of software components, close the gap between software and data engineering, and guide component selection. This thesis aims to improve the current state of software engineering by bringing together these different points of view and providing in- sightful analysis and useful suggestions for the effective use of knowledge-based systems in choosing software components.
dc.description.sponsorshipUtrecht University
dc.language.isoEN
dc.subjectIt's a recommendation system based on AI for the software packages.
dc.titleComponent recommendation system
dc.type.contentMaster Thesis
dc.rights.accessrightsOpen Access
dc.subject.keywordssoftware; package; recommendation; MCDM; AI; package repository;
dc.subject.courseuuArtificial Intelligence
dc.thesis.id29563


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