Heuristic evaluation of user interfaces
CHI '90 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Integrating obstacles in goal-driven requirements engineering
Proceedings of the 20th international conference on Software engineering
The use of goals to surface requirements for evolving systems
Proceedings of the 20th international conference on Software engineering
Augmenting shared personal calendars
Proceedings of the 15th annual ACM symposium on User interface software and technology
ScenIC: A Strategy for Inquiry-Driven Requirements Determination
RE '99 Proceedings of the 4th IEEE International Symposium on Requirements Engineering
Integrating Meeting Capture within a Collaborative Team Environment
UbiComp '01 Proceedings of the 3rd international conference on Ubiquitous Computing
Towards Modeling and Reasoning Support for Early-Phase Requirements Engineering
RE '97 Proceedings of the 3rd IEEE International Symposium on Requirements Engineering
Privacy policies as decision-making tools: an evaluation of online privacy notices
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Privacy risk models for designing privacy-sensitive ubiquitous computing systems
DIS '04 Proceedings of the 5th conference on Designing interactive systems: processes, practices, methods, and techniques
Privacy practices of Internet users: self-reports versus observed behavior
International Journal of Human-Computer Studies - Special isssue: HCI research in privacy and security is critical now
Designing for privacy in interactive systems
Designing for privacy in interactive systems
Design for privacy in ubiquitous computing environments
ECSCW'93 Proceedings of the third conference on European Conference on Computer-Supported Cooperative Work
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We introduce the concept of augmentation methods, methods that complement other methods by addressing specific non-functional requirements (NFRs). Since most projects do not have dedicated expertise in all relevant NFRs most team members may be comparative novices for that class of NFR. STRAP is a lightweight goal-refinement method for analyzing privacy NFRs. We describe it briefly and then present three experiments to assess its effectiveness and that of several existing privacy frameworks. We analyze the results in terms of method efficiency: the number of analysts needed to find a given proportion of benchmark problems. The alternative methods are generally effective in identifying privacy vulnerabilities but they are inefficient, since the average analyst misses many potential problems. In three distinct application domains, STRAP led to equal or better identification of privacy vulnerabilities and was in all cases more efficient. We conclude that a combination of lightweight structuring and heuristic appropriateness is the reason for these advantages.