Software Engineering for Usable Mobile Privacy Management

The overall aim of the this Microsoft funded SEIF project is to provide software engineers with tools to understand privacy requirements for mobile applications and to help engineer these into applications that may evolve at design time and will certainly adapt at runtime.

Our vision is to provide software developers tools to help them understand and support the users of their mobile applications. A key innovation of these tools will be support for provision and maintenance of links between what users, or privacy policies, say about privacy and what the software actually does. The project delivered a tool-supported argumentation language to express and reason about dynamic and personal privacy requirements of mobile users. The software engineering framework provided a synchronous support for the traceability between privacy requirements and mobile code to control the disclosure of information to the right people under meaningful contexts. A simulation of varying awareness settings of persona's helps software engineers to gain a better understanding of privacy requirements in the social settings.


Bashar Nuseibeh Arosha Bandara Blaine Price Yijun Yu Thein Than Tun Charles B. Haley Inah Omoronyia


  • mct
  • blinkit
  • security & privacy arguments
  • Publications

  • Tun, Thein Than; Bandara, Arosha K.; Price, Blaine A.; Yu, Yijun; Haley, Charles; Omoronyia, Inah and Nuseibeh, Bashar (2012). Privacy arguments: analysing selective disclosure requirements for mobile applications. In: 20th IEEE International Requirements Engineering Conference, 24-28 September 2012 , Chicago, Illinois.
  • Yu, Yijun; Lin, Yu; Hu, Zhenjiang; Hidaka, Soichiro; Hiroyuki, Kato and Montrieux, Lionel. "Maintaining invariant traceability through bidirectional transformations", In: 34th International Conference on Software Engineering, 02-09 June 2012, Zurich.
  • Yijun Yu, Thein Than Tun, and Bashar Nuseibeh (2011). "Specifying and detecting meaningful changes in programs". In: 26th IEEE/ACM International Conference On Automated Software Engineering, 6-11 Nov 2011, Lawrence, Kansas, USA, pp. 273--282.
  • Yijun Yu, Arosha Bandara, Thein Thun Tun, and Bashar Nuseibeh. "Towards Learning to Detect Meaningful Changes in Software", In: Proceedings of International Workshop on Machine Learning Technologies in Software Engineering (MALETS'11), 2011.