Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/66680
Title: GitHub repository analysis & prediction
Authors: Li, Shing To
Keywords: DRNTU::Business::International business::Data processing
DRNTU::Engineering::Computer science and engineering::Information systems::Information systems applications
Issue Date: 2016
Abstract: GitHub is a popular hosting service for software projects boasting over 35 million repositories. Many software projects today rely upon reusing existing Open Source projects in the form of a starting reference or as a package dependency. Bad software dependencies may impact a project in the long run. This project aims to use data mining to uncover patterns and discover new knowledge on what makes a repository healthy. To apply the results of this finding, a web application that uses the results of this analysis has been built and provides prediction for a GitHub repository. This web application can be visited at http://gitvital.ddns.net while the server is online.
URI: http://hdl.handle.net/10356/66680
Rights: Nanyang Technological University
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Student Reports (FYP/IA/PA/PI)

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