Over the past decade, goal models have been used in Computer Science in order to represent software requirements, business objectives and design qualities. Such models extend traditional AI planning techniques for representing goals by allowing for partially defined and possibly inconsistent

, such as goals to be achieved, agents to be assigned, alternatives to be negotiated, etc. The paper presents an approach to requirements acquisition which is driven by such higher-level concepts. Requirements models are acquired as instances of a conceptual meta-model. The latter can be represented as a graph

Even though goal modelling is an effective approach to requirements engineering, it is known to present a number of difficulties in practice. The paper discusses these difficulties and proposes to couple goal modelling and scenario authoring to overcome them. Whereas existing techniques use

Abstract—Goal models capture stakeholder requirements for a system-to-be, but also circumscribe a space of alternative specifications for fulfilling these requirements. Recent proposals for self-adaptive software systems rely on variants of goal models to support monitoring and adaptation functions

The goal of visual modeling research is to develop mathematical models and associated algorithms for the analysis and synthesis of visual information. Image analysis and synthesis characterize the domains of computer vision and computer graphics, respectively. For nearly three decades, the vision

Representation and reasoning about information system (IS) requirements is facilitated with the use of goal models to describe the desired and undesired IS behaviors. One difficulty in goal modeling is arriving at a shared understanding of a goal model instance, mainly due to different backgrounds

We describe a method for reducing the complexity of temporal logic model checking in systems composed of many parallel processes. The goal is to check properties of the components of a system and then deduce global properties from these local properties. The main difficulty with this type

Over the past decade, goal models have been used in Computer Science in order to represent software requirements, business objectives and design qualities. Such models extend traditional AI planning techniques for representing goals by allowing for partially defined and possibly inconsistent

Existing models for describing a process (such as a business process or a software development process) tend to focus on the \what " or the \how " of the process. For example, a health insurance claim process would typically be described in terms of a number of steps for assessing

Abstract. Goal models are theories that describe how various stakeholder goals relate to each other. The constructs that such models use to represent these re-lationships focus on characterizing the nature of causality that connects goals, without, however, including temporal aspects