Reasoning about partial goal satisfaction for requirements and design engineering.

Exploring alternative options is at the heart of the requirements and design processes. Different alternatives contribute to different degrees of achievement of non-functional goals about system safety, security, performance, usability, and so forth. Such goals in general cannot be satisfied in an absolute, clear-cut sense. Various qualitative and quantitative frameworks have been proposed to support the assessment of alternatives for design decision making. In general they lead to limited conclusions due to the lack of accuracy and measurability of goal formulations and the lack of impact propagation rules along goal contribution links. The paper presents techniques for specifying partial degrees of goal satisfaction and for quantifying the impact of alternative system designs on the degree of goal satisfaction. The approach consists in enriching goal refinement models with a probabilistic layer for reasoning about partial satisfaction. Within such models, non-functional goals are specified in a precise, probabilistic way; their specification is interpreted in terms of application-specific measures; impact of alternative goal refinements is evaluated in terms of refinement equations over random variables involved in the system's functional goals. A systematic method is presented for guiding the elaboration of such models. The latter can then be used to assess the impact of alternative decisions on the degree of goal satisfaction or to derive quantitative, fine-grained requirements on the software to achieve the higher-level goals.