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Sinha Vinayak PDF A APPROVED.pdf (1.37 MB)

ETD Abstract Container

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Sentiment Analysis On Java Source Code In Large Software Repositories

Sinha, Vinayak
http://orcid.org/0000-0003-4792-254X
http://rave.ohiolink.edu/etdc/view?acc_num=ysu1464880227

Abstract Details

2016, Master of Computing and Information Systems, Youngstown State University, Department of Computer Science and Information Systems.
While developers are writing code to accomplish the task assigned to them, their sentiments play a vital role and have a massive impact on quality and productivity. Sentiments can have either a positive or a negative impact on the tasks being performed by developers. This thesis presents an analysis of developer commit logs for GitHub projects. In particular, developer sentiment in commits is analyzed across 28,466 projects within a seven-year time frame. We use the Boa infrastructure’s online query system to generate commit logs as well as files that were changed during the commit. Two existing sentiment analysis frameworks (SentiStrength and NLTK) are used for sentiment extraction. We analyze the commits in three categories: large, medium, and small based on the number of commits using sentiment analysis tools. In addition, we also group the data based on the day of week the commit was made and map the sentiment to the file change history to determine if there was any correlation. Although a majority of the sentiment was neutral, the negative sentiment was about 10% more than the positive sentiment overall. Tuesdays seem to have the most negative sentiment overall. In addition, we do find a strong correlation between the number of files changed and the sentiment expressed by the commits the files were part of. It was also observed that SentiStrength and NLTK show consistent results and similar trends. Future work and implications of these results are discussed.
Bonita Sharif, PhD (Advisor)
Alina Lazar, PhD (Committee Member)
John Sullins, PhD (Committee Member)
71 p.
Computer Science; Information Technology; Organizational Behavior
Sentiment Analysis; Emotions; Commit logs; Java projects; Large Software Repositories

Recommended Citations

Citations

  • Sinha, V. (2016). Sentiment Analysis On Java Source Code In Large Software Repositories [Master's thesis, Youngstown State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=ysu1464880227

    APA Style (7th edition)

  • Sinha, Vinayak. Sentiment Analysis On Java Source Code In Large Software Repositories. 2016. Youngstown State University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=ysu1464880227.

    MLA Style (8th edition)

  • Sinha, Vinayak. "Sentiment Analysis On Java Source Code In Large Software Repositories." Master's thesis, Youngstown State University, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=ysu1464880227

    Chicago Manual of Style (17th edition)

ysu1464880227
16,362
© 2016, all rights reserved.
This open access ETD is published by Youngstown State University and OhioLINK.