A Taxonomy for Mining and Classifying Privacy Requirements in Issue Reports
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Digital and physical footprints are a trail of user activities collected over the use of software applications and systems. As software becomes ubiquitous, protecting user privacy has become challenging. With the increasing of user privacy awareness and advent of privacy regulations and policies, there is an emerging need to implement software systems that enhance the protection of personal data processing. However, existing privacy regulations and policies only provide high-level principles which are difficult for software engineers to design and implement privacy-aware systems. In this paper, we develop a taxonomy that provides a comprehensive set of privacy requirements based on two well-established and widely-adopted privacy regulations and frameworks, the General Data Protection Regulation (GDPR) and the ISO/IEC 29100. These requirements are refined into a level that is implementable and easy to understand by software engineers, thus supporting them to attend to existing regulations and standards. We have also performed a study on how two large open-source software projects (Google Chrome and Moodle) address the privacy requirements in our taxonomy through mining their issue reports. The paper discusses how the collected issues were classified, and presents the findings and insights generated from our study.
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