The success of large software engineering projects depends critically on the specification, which must represent the requirements of a large number of people with widely differing perspectives. Conventional approaches to software engineering do not address the process of identifying and integrating these perspectives, but instead concentrate on the maintenance of a single consistent description. This results in a specification which represents only one point of view, often the analyst's, excluding suggestions which do not fit with this view. The processes which led to the adoption of this point of view will go unrecorded, making any rationale attached to such a specification incomplete. Other participants will not be able to validate it properly, as it does not relate to their requirements. This thesis integrates ideas drawn from the study of knowledge acquisition, computer-supported co-operative work and negotiation into a model of the specification activity which allows the capture ...

Hybrid knowledge representation formalisms consist of two or more different subformalisms for representing different kinds of knowledge or knowledge in different kinds of representation formats. For a semantically well-founded hybrid formalism not only a precise semantics for each of the participating subformalisms has to be given but a semantics for the interrelationship between these subformalisms as well. A hybrid representation system therefore has to be implemented as a hybrid reasoning system taken into account these semantic models. The BACK system as an instance of this class of systems will be described with respect to the underlying semantic model and the demands for a reasoning component as one part of the realization of the formalism. The consequences and limits for the implementation of the BACK system are discussed. 1 Introduction Aaron Sloman pointed out very clearly in [22] the need for different knowledge representation formalisms for the adequate representation of a...

Efficiency dictates that plans for large-scale distributed activities be revised incrementally, with parts of plans being revised only if the expected utility of identifying and revising the subplans improve on the expected utility of using the original plan. The problems of identifying and reconsidering the subplans affected by changed circumstances or goals are closely related to the problems of revising beliefs as new or changed information is gained. But the current techniques of reason maintenance--- the standard method for belief revision---choose revisions arbitrarily and enforce global notions of consistency and groundedness which may mean reconsidering all beliefs or plan elements at each step. We outline revision methods that revise only those beliefs and plans worth revising, and that tolerate incoherence and ungroundedness when these are judged less detrimental than a costly revision effort. 1 Introduction Planning is necessary for the organization of large-scale activitie...

Efficiency dictates that plans for large-scale distributed activities be revised incrementally, with parts of plans being revised only if the expected utility of identifying and revising the subplans improves on the expected utility of using the original plan. The problems of identifying and reconsidering the subplans affected by changed circumstances or goals are closely related to the problems of revising beliefs as new or changed information is gained. But traditional techniques of reason maintenance---the standard method for belief revision---choose revisions arbitrarily and enforce global notions of consistency and groundedness which may mean reconsidering all beliefs or plan elements at each step. To address these problems, we developed (1) revision methods aimed at revising only those beliefs and plans worth revising, and tolerating incoherence and ungroundedness when these are judged less detrimental than a costly revision effort, (2) an artificial market economy in planning an...

Hybrid knowledge representation and reasoning systems have received a lot of interest in recent years. In this paper, we will give a brief survey of the principles and ideas behind these systems and will then focus on one particular kind of such systems, namely, TBox/ABox systems. A formal analysis of these systems clarifies some of the subtleties and problems involved. Finally, the computational problems are investigated, which leads to two conclusions. First, worst-case tractability cannot be achieved in TBox/ABox systems. Second, even if some system-component uses only incomplete reasoning methods, it is nevertheless possible to achieve completeness in the overall system in certain special cases. 1 Introduction Hybrid knowledge representation and reasoning systems (KRR systems) are systems that use more than one representation formalism and/or more than one reasoning component. Such a design addresses two important issues in current research on knowledge representation and reasonin...

Efficiency dictates that plans for large-scale distributed activities be revised incrementally, with parts of plans being revised only if the expected utility of identifying and revising the subplans improve on the expected utility of using the original plan. The problems of identifying and reconsidering the subplans affected by changed circumstances or goals are closely related to the problems of revising beliefs as new or changed information is gained. But traditional techniques of reason maintenance---the standard method for belief revision---choose revisions arbitrarily and enforce global notions of consistency and groundedness which may mean reconsidering all beliefs or plan elements at each step. We develop revision methods aiming to revise only those beliefs and plans worth revising, and to tolerate incoherence and ungroundedness when these are judged less detrimental than a costly revision effort. We use an artificial market economy in planning and revision tasks to arrive at o...

The interaction of pattern-directed invocation with equality in an automated reasoning system gives rise to a completeness problem. In such systems, a demon needs to be invoked not only when its pattern exactly matches a term in the reasoning data base, but also when it is possible to create a variant that matches.

A scenario is used to illustrate the capabilities of a proposed Design Apprentice, focussing on the area of detailed, low-level design. Given a specification, the Design Apprentice will be able to make many of the design decisions needed to synthesize the required program. The Design Apprentice will also be able to detect various kinds of contradictions and omissions in a specifica- tion.

We provide a detailed overview of knowledge representation issues in general and terminological knowledge representation in particular. Terminological knowledge representation, which originated with KL-ONE, is an object-centered approach in the tradition of semantic networks and frames. Terminological systems share three distinguishing characteristics: (1) They are intended to support the definition of conceptual terms comprising a "terminology" and to facilitate reasoning about such terms. As such, they are explicitly distinguished from assertional systems which make statements of fact based on some terminology. (2) Their concepts are arranged in a taxonomy so that the attributes of a concept apply to its descendants without exception. Thus, the proper location of any concept within the taxonomy can be uniquely determined from the concept's definition by an automatic process known as classification. (3) They restrict the expressiveness of their language to achieve relatively efficient...

The paper describes a knowledge-based framework for the development of program reverse and forward engineering. The substrate for this framework is an object-oriented environment for knowledge-based applications (XRL) written in Common Lisp. The approach starts from the idea that forward and reverse engineering are evolutive, knowledge intensive activities. Regarding the development of knowledge-based systems, knowledge acquisition is considered as a modelling activity that implies not only the evolution of the knowledge base of the system but also the evolution of the mental model that the human experts actually use. Therefore, an integrated collection of tools and techniques that support the construction, evolution, and usage of knowledge-based models of programming concepts and constructs are provided. An evolutive taxonomy of reusable program components related to programming concepts is also considered essential for the approach. One of the main applications written in the knowledge-based framework is the development of an intelligent reverse engineering system of FORTRAN programs. After obtaining a high level description of an analyzed program, this description may be refined to C or pseudocode. 2 1.