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| Can We Make it Better? Assessing and Improving Quality of GitHub Repositories |

| Gede Artha Azriadi PRANA PhD Candidate
School of Information Systems
Singapore Management University | Research Area
Dissertation Committee Chairman Committee Members |
| | Date
December 11, 2019 (Wednesday) | Time
2.00pm - 3.00pm | Venue
Meeting Room 4.4, Level 4,
School of Information Systems,
Singapore Management University
80 Stamford Road
Singapore 178902 | We look forward to seeing you at this research seminar. 
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| | About The Talk With over 34 million public repositories (and 100 million repositories in total), GitHub is the most popular platform for hosting software project repositories. It is widely used across various parts of the world, and for various kinds of projects ranging from small-scale personal projects to large projects with commercial backers. In this talk, we present two studies on characteristics of repositories on GitHub, which can subsequently be used to improve quality of projects on the platform. We begin by presenting result of our study on characteristics of GitHub README files, focusing on types of content and their distribution. As part of this work, we also developed a multi-label classifier to predict content type labels of sections of GitHub README file, which can be subsequently be used to improve quality and organization of README files. Secondly, we present the result of our study on characteristics of vulnerabilities in open-source dependencies of GitHub projects. For this work, we used an industrial-grade software composition analysis tools on 600 projects from 4 popular languages, and performed analysis on various aspects such as common vulnerability types, association between types, persistence of vulnerabilities, and potential relationship between vulnerabilities and project and commit attributes. We also propose ideas for further work along with points from several pertinent research in the field. | Speaker Biography Gede Artha Azriadi Prana is a PhD candidate in the School of Information Systems, Singapore Management University, under supervision of Associate Professor David Lo. He received his B.Eng. in Computer Engineering from Nanyang Technological University and M.Tech. in Knowledge Engineering from National University of Singapore. His research focuses on application of analytics to unstructured data in software engineering domain. Prior to his current study, he has worked in software engineering field for about a decade. |
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