  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.
