Comparing the effectiveness of reasoning formalisms for partial models
Proceedings of the Workshop on Model-Driven Engineering, Verification and Validation
Change propagation due to uncertainty change
FASE'13 Proceedings of the 16th international conference on Fundamental Approaches to Software Engineering
Evaluation of web-specific goal oriented requirements language models with quantitative reasoning
ACM SIGSOFT Software Engineering Notes
Uncertainty handling in goal-driven self-optimization - Limiting the negative effect on adaptation
Journal of Systems and Software
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Models are good at expressing information that is known but do not typically have support for representing what information a modeler does not know at a particular phase in the software development process. Partial models address this by being able to precisely represent uncertainty about model content. In previous work, we developed a general approach for defining partial models and applied it to capturing uncertainty, including reasoning over design models containing uncertainty. In this paper, we show how to apply our approach to managing requirements uncertainty. In particular, we address the problem of specifying uncertainty within a requirements model, refining a model as uncertainty reduces and reasoning with traceability relations between models containing uncertainty. We illustrate our approach using the meeting scheduler example.