GitHub repository analysis & prediction
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...
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| Other Authors: | |
| Format: | Final Year Project (FYP) |
| Language: | English |
| Published: |
2016
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| Subjects: | |
| Online Access: | http://hdl.handle.net/10356/66680 |
| _version_ | 1811681669825953792 |
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| author | Li, Shing To |
| author2 | Sourav Saha Bhowmick |
| author_facet | Sourav Saha Bhowmick Li, Shing To |
| author_sort | Li, Shing To |
| collection | NTU |
| description | 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. |
| first_indexed | 2024-10-01T03:44:37Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/66680 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T03:44:37Z |
| publishDate | 2016 |
| record_format | dspace |
| spelling | ntu-10356/666802023-03-03T20:32:30Z GitHub repository analysis & prediction Li, Shing To Sourav Saha Bhowmick School of Computer Engineering DRNTU::Business::International business::Data processing DRNTU::Engineering::Computer science and engineering::Information systems::Information systems applications 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. Bachelor of Engineering (Computer Science) 2016-04-21T00:48:06Z 2016-04-21T00:48:06Z 2016 Final Year Project (FYP) http://hdl.handle.net/10356/66680 en Nanyang Technological University 50 p. application/pdf |
| spellingShingle | DRNTU::Business::International business::Data processing DRNTU::Engineering::Computer science and engineering::Information systems::Information systems applications Li, Shing To GitHub repository analysis & prediction |
| title | GitHub repository analysis & prediction |
| title_full | GitHub repository analysis & prediction |
| title_fullStr | GitHub repository analysis & prediction |
| title_full_unstemmed | GitHub repository analysis & prediction |
| title_short | GitHub repository analysis & prediction |
| title_sort | github repository analysis prediction |
| topic | DRNTU::Business::International business::Data processing DRNTU::Engineering::Computer science and engineering::Information systems::Information systems applications |
| url | http://hdl.handle.net/10356/66680 |
| work_keys_str_mv | AT lishingto githubrepositoryanalysisprediction |