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The REVERE Project: Experiments with the Application of Probabilistic NLP to Systems Engineering

Authors
Publisher
Springer-Verlag,
Publication Date
Keywords
  • Qa75 Electronic Computers. Computer Science
Disciplines
  • Computer Science
  • Engineering
  • Linguistics

Abstract

The REVERE project The REVERE project: experiments with the application of probabilistic NLP to systems engineering Paul Rayson1, Luke Emmet2, Roger Garside1 and Pete Sawyer1 1Lancaster University, Lancaster, UK. LA1 4YR {paul, rgg, [email protected] 2Adelard, Coborn House, 3 Coborn Road, London UK. E3 2DA [email protected] Abstract. Despite natural language's well-documented shortcomings as a medium for precise technical description, its use in software-intensive systems engineering remains inescapable. This poses many problems for engineers who must derive problem understanding and synthesise precise solution descriptions from free text. This is true both for the largely unstructured textual descriptions from which system requirements are derived, and for more formal documents, such as standards, which impose requirements on system development processes. This paper describes experiments that we have carried out in the REVERE1 project to investigate the use of probabilistic natural language processing techniques to provide systems engineering support. 1. Introduction Despite natural language's well-documented shortcomings as a medium for precise technical description, its use in software-intensive systems engineering [1] (henceforth referred to simply as systems engineering) remains inescapable. The products of the systems engineering process (requirements specifications, acceptance test plans, etc.) almost always have to employ natural language in order to describe the desired system properties for a heterogeneous readership. Recognising this, several researchers [2, 3, 4, 5, 6, 7] have used natural language processing (NLP) tools for the analysis, paraphrasing and quality evaluation of documents produced by the systems engineering process. There has been little attention paid to the main focus of this paper, however: tools to assist the analysis of natural language inputs to systems engineering. In developing the requirements for a system, systems engineers face the n

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