The development of most large and complex systems necessarily involves many people - each with their own perspectives on the system defined by their knowledge, responsibilities, and commitments. To address this we have advocated distributed development of specifications from multiple perspectives. However, this leads to problems of identifying and handling inconsistencies between such perspectives. Maintaining absolute consistency is not always possible. Often this is not even desirable since this can unnecessarily constrain the development process, and can lead to the loss of important information. Indeed since the real-world forces us to work with inconsistencies, we should formalise some of the usually informal or extra-logical ways of responding to them. This is not necessarily done by eradicating inconsistencies but rather by supplying logical rules specifying how we should act on them. To achieve this, we combine two lines of existing research: the ViewPoints framew...

Large-scale software development is an evolutionary process. In an evolving specification, multiple development participants often hold multiple, inconsistent views on the system being developed, and considerable effort is spent handling recurrent inconsistencies. Detecting and resolving inconsistencies is only part of the problem: a resolved inconsistency might not stay resolved as a specification evolves. Frameworks in which inconsistency is tolerated help by allowing resolution to be delayed. However, the evolution of a specification may affect both resolved and unresolved inconsistencies. We present and elaborate a framework in which software development knowledge is partitioned into multiple views called "ViewPoints". Inconsistencies between ViewPoints are managed by explicitly representing relationships between them, and recording both resolved and unresolved inconsistencies. We assume that ViewPoints will often be inconsistent with one another, and we ensure that a complete wor...

We present the syntax and proof theory of a logic of argumentation, LA. We also outline the development of a category theoretic semantics for LA. LA is the core of a proof theoretic model for reasoning under uncertainty. In this logic, propositions are labelled with a representation of the arguments which support their validity. Arguments may then be aggregated to collect more information about the potential validity of the propositions of interest. We make the notion of aggregation primitive to the logic, and then define strength mappings from sets of arguments to one of a number of possible dictionaries. This provides a uniform framework which incorporates a number of numerical and symbolic techniques for assigning subjective confidences to propositions on the basis of their supporting arguments. These aggregation techniques are also described, with examples. Key words: Uncertain reasoning, epistemic probability, argumentation, non-classical logics, non-monotonic reasoning 1. Introd...

This paper surveys methods for representing and reasoning with imperfect information. It opens with an attempt to classify the different types of imperfection that may pervade data, and a discussion of the sources of such imperfections. The classification is then used as a framework for considering work that explicitly concerns the representation of imperfect information, and related work on how imperfect information may be used as a basis for reasoning. The work that is surveyed is drawn from both the field of databases and the field of artificial intelligence. Both of these areas have long been concerned with the problems caused by imperfect information, and this paper stresses the relationships between the approaches developed in each.

In an evolving specification, considerable development time and effort is spent handling recurrent inconsistencies. Tools and techniques for detecting and resolving inconsistencies only address part of the problem: they do not ensure that a resolution generated at a particular stage will apply at all subsequent stages of the specification process. Previously, we have advocated tolerance and management of inconsistency, rather than strict enforcement of consistency. The advantages of this approach include the ability to delay resolution, facilitation of concurrent development, and greater flexibility in development strategies. However, this approach does not prevent inconsistencies themselves from evolving, and it does not ensure that resolved inconsistencies remain resolved throughout subsequent developments. We address these problems by explicitly recording relationships between partial specifications (ViewPoints), representing both resolved and unresolved inconsistencies. ...

The development of software systems inevitably involves the detection and handling of inconsistencies. These inconsistencies can arise in system requirements, design specifications and, quite often, in the descriptions that form the final implemented software product. A large proportion of software engineering research has been devoted to consistency maintenance, or geared towards eradicating inconsistencies as soon as they are detected. Software practitioners, on the other hand, live with inconsistency as a matter of course. Depending on the nature of an inconsistency, its causes and its impact, they sometimes choose to tolerate its presence, rather than resolve it immediately, if at all.

The development of software systems involves the detection and handling of inconsistencies. These inconsistencies arise in system requirements, design specifications and, quite often, in the descriptions that form the final implemented software product. This paper presents a critical review of approaches that explicitly tolerate and manage inconsistencies, and explores different kinds of inconsistencies that arise during different stages of software development. Managing inconsistency refers not only to the detection and removal of inconsistencies, but also to activities that facilitate continued development in their presence. Such activities include procedures for controlled amelioration or avoidance of inconsistency, which in turn may require analysis and reasoning in the presence of inconsistency.

: Argumentation is the process of constructing arguments about propositions, and the assignment of statements of confidence to those propositions based on the nature and relative strength of their supporting arguments. The process is modelled as a labelled deductive system, in which propositions are doubly labelled with the grounds on which they are based and a representation of the confidence attached to the argument. Argument construction is captured by a generalised argument consequence relation based on the !- fragment of minimal logic.. Arguments can be aggregated by a variety of numeric and symbolic flattening functions. This approach appears to shed light on the common logical structure of a variety of quantitative, qualitative and defeasible uncertainty calculi. Introduction Probability theory is the most widely accepted mathematical framework for reasoning under uncertainty. However questions about its universal applicability have often been raised. Before 1606, when Pascal...

Relationships among different modeling perspectives have been systematically investigated focusing either on given notations (e.g. UML) or on domain reference models (e.g. ARIS/SAP). In contrast, many successful informal methods for business analysis and requirements engineering (e.g. JAD) emphasize team negotiation, goal orientation and flexibility of modeling notations. This paper addresses the question how much formal and computerized support can be provided in such settings without destroying their creative tenor. Our solution is based on a novel modeling language design, M-Telos, that integrates the adaptability and analysis advantages of the logic-based meta modeling language Telos with a module concept covering the structuring mechanisms of scalable software architectures. It comprises four components: (1) A modular conceptual modeling formalism organizes individual perspectives and their interrelationships. (2) Perspective schemata are linked to a conceptual meta meta...

The use of logic in identifying and analysing inconsistency in requirements from multiple stakeholders has been found to be effective in a number of studies. Default reasoning is a theoretically well founded formalism that is especially suited for supporting the evolution of requirements. However, direct use of logic in eliciting requirements and in discussing them with stakeholders poses serious useability problems. In this paper we explore the integration of natural language parsing techniques with default reasoning to overcome these difficulties. We also propose a method for automatically discovering scenarios that expose inconsistencies in requirements, and show how to deal with them in a formal manner. These techniques were implemented and tested in a prototype tool called CARL.