• Login
    View Item 
    •   Shocker Open Access Repository Home
    • Graduate Student Research
    • ETD: Electronic Theses and Dissertations
    • Master's Theses
    • View Item
    •   Shocker Open Access Repository Home
    • Graduate Student Research
    • ETD: Electronic Theses and Dissertations
    • Master's Theses
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Source code comments under good and bad lenses, and their association with software quality: an empirical investigation on open source software

    View/Open
    Thesis (1.298Mb)
    Date
    2019-05
    Author
    Liu, Lifei
    Advisor
    Kagdi, Huzefa Hatimbhai
    Metadata
    Show full item record
    Abstract
    Comments are ubiquitous in source code of real software systems. Software developers rely on them for comprehending and evolving software systems, i.e., to add new features and fix bugs. They imbibe the practice of commenting code from their formative years. Therein lies the critical questions for which scientific answers are largely and strikingly absent: “how prevalent are good and bad comments in production code, e.g., open source software?” or “do developers agree on their usefulness, e.g., with varied levels of experience?” Are these issues a matter of pure vanity or do they bear substance, e.g., do comments associate, if at all, with software complexity and quality, and to what extent, e.g., cohesion and coupling metrics? Answers to these questions directly influence developer communication and productivity, and software cost, reliability, and quality. This work conducted a series of rigorous empirical studies in quest of initial answers to the above stated questions. Both quantitative and qualitative investigations were performed. Our results from six open source projects show that although 60% of source code comments are good, there are 40% bad comments (with a supermajority agreement). Not all developers always agree on the goodness or badness of specific comments. We also investigated the correlation between object-oriented complexity, cohesion, and coupling metrics with the source code comments. We did find evidence for increased levels of comments with low quality and/or high-complexity code. Future work entails the automatic classification of source code comments into a taxonomy of good and bad comments, and to formulate approaches to prevent and eliminate bad comments (e.g., refactor code reeking with bad comment).
    Description
    Thesis (M.S.)-- Wichita State University, College of Engineering, Dept. of Electrical Engineering and Computer Science
    URI
    http://hdl.handle.net/10057/16407
    Collections
    • CE Theses and Dissertations
    • EECS Theses and Dissertations
    • Master's Theses

    Browse

    All of Shocker Open Access RepositoryCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsBy TypeThis CollectionBy Issue DateAuthorsTitlesSubjectsBy Type

    My Account

    LoginRegister

    Statistics

    Most Popular ItemsStatistics by CountryMost Popular Authors

    DSpace software copyright © 2002-2023  DuraSpace
    DSpace Express is a service operated by 
    Atmire NV