Browsing by Author "Davis, James C."

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    An Exploratory Mixed-methods Study on General Data Protection Regulation (GDPR) Compliance in Open-Source Software
    Franke, Lucas; Liang, Huayu; Farzanehpour, Sahar; Brantly, Aaron F.; Davis, James C.; Brown, Chris (ACM, 2024-10-24)
    Background: Governments worldwide are considering data privacy regulations. These laws, such as the European Union’s General Data Protection Regulation (GDPR), require software developers to meet privacy-related requirements when interacting with users’ data. Prior research describes the impact of such laws on software development, but only for commercial software. Although opensource software is commonly integrated into regulated software, and thus must be engineered or adapted for compliance, we do not know how such laws impact open-source software development. Aims: To understand how data privacy laws affect open-source software (OSS) development, we focus on the European Union’s GDPR, as it is the most prominent such law. We investigated how GDPR compliance activities influence OSS developer activity (RQ1), how OSS developers perceive fulfilling GDPR requirements (RQ2), the most challenging GDPR requirements to implement (RQ3), and how OSS developers assess GDPR compliance (RQ4). Method:We distributed an online survey to explore perceptions of GDPR implementations from open-source developers (N=56). To augment this analysis, we further conducted a repository mining study to analyze development metrics on pull requests (N=31,462) submitted to open-source GitHub repositories. Results: Our results suggest GDPR policies complicate OSS development and introduce challenges, primarily regarding the management of users’ data, implementation costs and time, and assessments of compliance. Moreover, we observed negative perceptions of the GDPR from OSS developers and significant increases in development activity, in particular metrics related to coding and reviewing, on GitHub pull requests related to GDPR compliance. Conclusions: Our findings provide future research directions and implications for improving data privacy policies, motivating the need for relevant resources and automated tools to support data privacy regulation implementation and compliance efforts in OSS.
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    Fast and accurate incremental feedback for students' software tests using selective mutation analysis
    Kazerouni, Ayaan M.; Davis, James C.; Basak, Arinjoy; Shaffer, Clifford A.; Servant Cortes, Francisco Javier; Edwards, Stephen H. (2021-05)
    As incorporating software testing into programming assignments becomes routine, educators have begun to assess not only the correctness of students' software, but also the adequacy of their tests. In practice, educators rely on code coverage measures, though its shortcomings are widely known. Mutation analysis is a stronger measure of test adequacy, but it is too costly to be applied beyond the small programs developed in introductory programming courses. We demonstrate how to adapt mutation analysis to provide rapid automated feedback on software tests for complex projects in large programming courses. We study a dataset of 1389 student software projects ranging from trivial to complex. We begin by showing that although the state-of-the-art in mutation analysis is practical for providing rapid feedback on projects in introductory courses, it is prohibitively expensive for the more complex projects in subsequent courses. To reduce this cost, we use a statistical procedure to select a subset of mutation operators that maintains accuracy while minimizing cost. We show that with only 2 operators, costs can be reduced by a factor of 2-3 with negligible loss in accuracy. Finally, we evaluate our approach on open-source software and report that our findings may generalize beyond our educational context. (c) 2021 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
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    A First Look at the General Data Protection Regulation (GDPR) in Open-Source Software
    Franke, Lucas; Liang, Huayu; Brantly, Aaron F.; Davis, James C.; Brown, Chris (ACM, 2024-04-14)
    This poster describes work on the General Data Protection Regulation (GDPR) in open-source software. Although open-source software is commonly integrated into regulated software, and thus must be engineered or adapted for compliance, we do not know how such laws impact open-source software development. We surveyed open-source developers (N=47) to understand their experiences and perceptions of GDPR. We learned many engineering challenges, primarily regarding the management of users’ data and assessments of compliance. We call for improved policy-related resources, especially tools to support data privacy regulation implementation and compliance in open-source software.