dc.rights.license | CC-BY-NC-ND | |
dc.contributor.advisor | Farshidi, S. | |
dc.contributor.author | Beigzadeh, Parsa | |
dc.date.accessioned | 2024-03-28T00:02:48Z | |
dc.date.available | 2024-03-28T00:02:48Z | |
dc.date.issued | 2024 | |
dc.identifier.uri | https://studenttheses.uu.nl/handle/20.500.12932/46213 | |
dc.description.abstract | The 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.sponsorship | Utrecht University | |
dc.language.iso | EN | |
dc.subject | It's a recommendation system based on AI for the software packages. | |
dc.title | Component recommendation system | |
dc.type.content | Master Thesis | |
dc.rights.accessrights | Open Access | |
dc.subject.keywords | software; package; recommendation; MCDM; AI; package repository; | |
dc.subject.courseuu | Artificial Intelligence | |
dc.thesis.id | 29563 | |