Attempto Controlled English — Not Just Another Logic Specification Language

Fuchs, Norbert E.; Schwertel, Uta; Schwitter, Rolf

doi:10.1007/3-540-48958-4_1

Cited by 87 publications

(50 citation statements)

References 15 publications

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“…); -achieve traceability as from the first documents produced; -manage more efficiently the problem of the changing user requirements. 10 As regards the possible applications of NLP systems to requirements engineering, it is worth noting that they are able to process both vocal and textual input, sometimes imposing restrictions such as limiting the vocabulary or the grammar.…”

Section: The Role Of Natural Language In Requirements Engineeringmentioning

confidence: 99%

Market research for requirements analysis using linguistic tools

Mich

MariangelaFranch

PierluigiInverardi

2004

Requirements Engineering

123

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Numerous studies in recent months have proposed the use of linguistic instruments to support requirements analysis. There are two main reasons for this: (i) the progress made in natural language processing, (ii) the need to provide the developers of software systems with support in the early phases of requirements definition and conceptual modelling. This paper presents the results of an online market research intended (a) to assess the economic advantages of developing a CASE tool that integrates linguistic analysis techniques for documents written in natural language, and (b) to verify the existence of potential demand for such a tool. The research included a study of the language -ranging from completely natural to highly restricted -used in documents available for requirements analysis, an important factor given that on a technological level there is a trade-off between the language used and the performance of the linguistic instruments. To determine the potential demand for such tool, some of the survey questions dealt with the adoption of development methodologies and consequently with models and support tools; other questions referred to activities deemed critical by the companies involved. Through statistical correspondence analysis of the responses, we were able to outline two "profiles" of companies that correspond to two potential market niches which are characterised by their very different approach to software development.

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Section: The Role Of Natural Language In Requirements Engineeringmentioning

confidence: 99%

Market research for requirements analysis using linguistic tools

Mich

MariangelaFranch

PierluigiInverardi

2004

Requirements Engineering

123

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“…Due to its limitations, it needs to be supported by a predictive (structural) editor which is Ontorion FluentEditor tool [25]. The other, well-known implementation of a controlled natural language is "Attempto Controlled English (ACE)" [26], developed by the University of Zurich. However, the origins of CNL can be found in the famous novel by George Orwell: "1984", where he discusses the NEWSPEAK -a controlled language.…”

Section: Programming Agents With Natural Languagementioning

confidence: 99%

Cognitum Ontorion: Knowledge Representation and Reasoning System

Weichbroth¹

2015

Annals of Computer Science and Information Systems

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Abstract-"If knowledge can create problems, it is not through ignorance that we can solve them." (Isaac Asimov). Nevertheless, at any point of human activity, knowledge (besides practice) is a key factor in understanding and solving any given problem. Nowadays, computer systems have the ability to support their users in an efficient and reliable way. In this paper we present and describe the functionality of the Cognitum Ontorion system. Firstly, we identify emerging issues focused on knowledge representation and reasoning. Secondly, we briefly discuss models and methodology of agent-oriented analysis and design. Next, the semantic knowledge management framework of the system is reviewed. Finally, the usability of Ontorion is argued based on a case study, in which a software process simulation modeling environment is developed. At the end we provide future work directions and final conclusions.

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“…the rules or formulas they consist of should be expressible in a controlled language [15,9], i.e. in a non-ambiguous language resembling natural language.…”

Section: Engineering and Renderingmentioning

confidence: 99%