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An Empirical Study Investigating Source Code Summarization Using Multiple Sources of Information

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2018, Master of Computing and Information Systems, Youngstown State University, Department of Computer Science and Information Systems.
Software developers depend on good source code documentation to understand existing source code to perform various tasks such as fixing bugs and implementing new features. Manual documentation by developers is often missing or outdated. Past research has suggested automatic code summarization tools to remedy this problem. While several works on source code summarization leveraged only source code to generate summaries, very little work exists on using other information sources. A lot of tacit knowledge is exchanged between developers in discussion forums or bug reporting sites that can be very useful for summarization. The novelty of our work is that we conducted an empirical study using eye tracking equipment to investigate the effects of four different types of information sources namely, source code, Stack Overflow, bug reports and their combination on code summarization, to understand how developers perform using these multiple sources of information during code summarization tasks. Each participant is asked to summarize four code elements in their own words using different contexts. We evaluate the summaries against a human oracle to find similarities and analyze the developers' eye gaze patterns to see what they look for and how they switch between different contexts. Our results indicate that Stack Overflow and bug reports are as helpful as source code in supporting code summarization tasks. Participants were more confident when using Stack Overflow and bug reports when compared to source code. The results of our study can be useful to researchers and practitioners interested in building context-aware code summarization tools that can help augment official documentation with the insightful information extracted from multiple sources.
Bonita Sharif, PhD (Advisor)
Abdu Arslanyilmaz, PhD (Committee Member)
Feng Yu, PhD (Committee Member)
118 p.

Recommended Citations

Citations

  • Sama, S. (2018). An Empirical Study Investigating Source Code Summarization Using Multiple Sources of Information [Master's thesis, Youngstown State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=ysu1527673352984124

    APA Style (7th edition)

  • Sama, Sanjana. An Empirical Study Investigating Source Code Summarization Using Multiple Sources of Information. 2018. Youngstown State University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=ysu1527673352984124.

    MLA Style (8th edition)

  • Sama, Sanjana. "An Empirical Study Investigating Source Code Summarization Using Multiple Sources of Information." Master's thesis, Youngstown State University, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=ysu1527673352984124

    Chicago Manual of Style (17th edition)