Requirements analysis includes a preliminary acquisition step where a global model for the specification of the system and its environment is elaborated. This model, called requirements model, involves concepts that are currently not supported by existing formal specification languages, 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 where each node captures an abstraction such as, e.g., goal, action, agent, entity, or event, and where the edges capture semantic links between such abstractions. Well-formedness properties on nodes and links constrain their instances - that is, elements of requirements models. Requirements acquisition processes then correspond to particular ways of traversing the meta-model graph to acquire approp...

Abstract. Requirements engineering is concerned with the identification of high-level goals to be achieved by the system envisioned, the refinement of such goals, the operationalization of goals into services and constraints, and the assignment of responsibilities for the resulting requirements to agents such as humans, devices and programs. Goal refinement and operationalization is a complex process which is not well supported by current requirements engineering technology. Ideally some form of formal support should be provided, but formal methods are difficult and costly to apply at this stage. This paper presents an approach to goal refinement and operationalization which is aimed at providing constructive formal support while hiding the underlying mathematics. The principle is to reuse generic refinement patterns from a library structured according to strengthening/weakening relationships among patterns. The patterns are once for all proved correct and complete. They can be used for guiding the refinement process or for pointing out missing elements in a refinement. The cost inherent to the use of a formal method is thus reduced significantly. Tactics are proposed to the requirements engineer for grounding pattern selection on semantic criteria. The approach is discussed in the context of the multi-paradigm language used in the KAOS method; this language has an external semantic net layer for capturing goals, constraints, agents, objects and actions together with their links, and an inner formal assertion layer that includes a real-time temporal logic for the specification of goals and constraints. Some frequent refinement patterns are highlighted and illustrated through a variety of examples. The general principle is somewhat similar in spirit to the increasingly popular idea of design patterns, although it is grounded on a formal framework here. Keywords: Goal-driven requirements engineering, refinement,

This paper is part of a broader research program to explore a mechanizable model of software development based on algebraic specifications and specification morphisms. An algebraic specification (or simply a specification) defines a language and constrains its possible meanings via axioms and inference rules. Specifications can be used to express many kinds of software-related artifacts, including domain models (Srinivas(1991)), formal requirements (Astesiano and Wirsing (1987), Ehrig and Mahr (1990), Partsch (1990), Sannella and Tarlecki (1985)), programming languages (Broy et al. (1987), Goguen and Winkler (1988), Hoare (1989)), abstract data types (Goguen et al. (1978), Guttag and Horning (1978)), and abstract algorithms (Smith and Lowry (1990)). There has been much work on operations for constructing larger specifications from smaller specifications (Astesiano and Wirsing (1987), Burstall and Goguen (1977), Sannella and Tarlecki (1988)). A specification morphism translates the language of one specification into the language of another specification in a way that preserves theorems. Specification morphisms underlie several aspects of software development, including specification refine-

Formal specifications have been a focus of software engineering research for many years and have been applied in a wide variety of settings. Their industrial use is still limited but has been steadily growing. After recalling the essence, role, usage, and pitfalls of formal specification, the paper reviews the main specification paradigms to date and discuss their evaluation criteria. It then provides a brief assessment of the current strengths and weaknesses of today's formal specification technology. This provides a basis for formulating a number of requirements for formal specification to become a core software engineering activity in the future.

This paper addresses the problem of how to construct refinements of specifications formally and incrementally. The key idea is to use a taxonomy of abstract design concepts, each represented by a design theory. An abstract design concept is applied by constructing a specification morphism from its design theory to a requirement specification. Procedures for propagating constraints, computing colimits, and constructing specification morphisms provide computational support for this approach. Although we conjecture that classification generally applies to the incremental application of knowledge represented in a taxonomy of design theories, this paper mainly focuses on algorithm design theories and presents several examples of design by classification.

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: the experience of the French central Bank in terms of developing knowledge-based systems have led us to elaborate an environment of knowledge modelisation called CERISE. In this approach, we introduce a notion of module, issued from software engineering. This notion is fully formalised using algebraic abstract types. The main difference between this formalisation and the earlier ones (see (ML)2, KbsSF, KARL, among others) is that the formalisation process does not take place after but during the knowledge acquisition process. This paper shows the effects of using this formalisation both in the acquisition and reusability of knowledge. I INTRODUCTION A library of reusable problem-solving methods was seen as a strong advantage in favour of the KADS methodology ([WIE92], [WIE93]). Reusability is a significant argument to justify the investments necessited by employing such an abstract and complex methodology. At the French Central Bank, half a dozen of knowledge-based systems deal wit...