Reasoning with Constrained Goal Models

Goal models have been widely used in Computer Science to represent software requirements, business objectives, and design qualities. Existing goal modeling techniques, however, have shown limitations of expressiveness and/or tractability in coping with complex real-world problems. In this work we exploit advances in automated reasoning technologies, notably SMT solvers, to propose and formalize: (i) an extended notion of goal model, namely Constrained Goal Models (CGMs), which makes explicit the notion of goal refinement and allows for constraints and penalties/rewards over goals and their refinements; (ii) a novel set of automated reasoning functionalities over CGMs, allowing for automatically generating suitable refinements of input CGMs, under user-specified assumptions and constraints, that also optimize given penalty/reward functions. We have implemented these modeling and reasoning functionalities in a prototype tool, using the Optimization Modulo Theory solver OptiMathSAT as automated reasoning backend.