Software requirements engineering : a risk-driven approach
(2018)
Files
thesis.pdf
Open Access - Adobe PDF
- 12.63 MB
Details
- Authors
- Supervisors
- van Lamsweerde, Axel
- Abstract
- Requirements Engineering (RE) is concerned with the elicitation, evaluation, specification, analysis and evolution of the requirements on a software-intensive system. Risk analysis at RE time aims at anticipating adverse conditions preventing the system from achieving its mission. In goal-oriented RE, a goal model shows how the system's objectives contribute to each other. Obstacle analysis is a goal-oriented form of risk analysis aimed at increasing requirements completeness. An obstacle to a goal is a precondition for the non-satisfaction of this goal. An obstacle model shows how obstacles contribute to each other in preventing goals from being satisfied. Obstacle analysis iterates on the identification of obstacles, the assessment of their likelihood and criticality, and the control of likely and critical obstacles. The thesis presents a quantitative framework for assessing and controlling obstacles to probabilistic goals. The latter must be satisfied in a specified percentage of cases at least. In this framework, domain experts estimate the likelihood of fine-grained obstacles together with their uncertainty margins. These estimates are up-propagated through the obstacle and goal models in order to quantitatively determine the likelihood of obstacles and the severity of their consequences. Comparing the computed satisfaction rate of high-level goals in the model with their required satisfaction rate yields measures of obstacle criticality. Countermeasures to most likely and critical obstacles are then identified. Those maximizing the satisfaction rate of high-level goals while minimizing their cost are selected for integration into the goal model. Our techniques are extended to support runtime system self-adaptation towards better satisfaction of high-level goals.
- Affiliations
Citations
Cailliau, A. (2018). Software requirements engineering : a risk-driven approach. https://hdl.handle.net/2078.5/46592