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|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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|Amended Final Report||1.29 MB||Adobe PDF||View/Open|
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