A knowledge representation language for requirements engineering
Requirements engineering, the phase of software development where the users' needs are investigated, is more and more shifting its concern from the target system towards its environment. A new generation of languages is needed to support the definition of application domain knowledge and the be...
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Veröffentlicht in: | Proc. IEEE; (United States) 1986-10, Vol.74 (10), p.1431-1444 |
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creator | Dubois, E. Hagelstein, J. Lahou, E. Ponsaert, F. Rifaut, A. |
description | Requirements engineering, the phase of software development where the users' needs are investigated, is more and more shifting its concern from the target system towards its environment. A new generation of languages is needed to support the definition of application domain knowledge and the behavior of the universe around the computer. This paper assesses the applicability of classical knowledge representation techniques to this purpose. Requirements engineers insist, however, more on natural representation, whereas expert systems designers insist on efficient automatic use of the knowledge. Given this priority of expressiveness, two candidates emerge: the semantic networks and the techniques based on logic. They are combined in a language called the ERAE model, which is illustrated on examples, and compared to other requirements engineering languages. |
doi_str_mv | 10.1109/PROC.1986.13644 |
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IEEE; (United States)</title><addtitle>JPROC</addtitle><description>Requirements engineering, the phase of software development where the users' needs are investigated, is more and more shifting its concern from the target system towards its environment. A new generation of languages is needed to support the definition of application domain knowledge and the behavior of the universe around the computer. This paper assesses the applicability of classical knowledge representation techniques to this purpose. Requirements engineers insist, however, more on natural representation, whereas expert systems designers insist on efficient automatic use of the knowledge. Given this priority of expressiveness, two candidates emerge: the semantic networks and the techniques based on logic. 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IEEE; (United States)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Dubois, E.</au><au>Hagelstein, J.</au><au>Lahou, E.</au><au>Ponsaert, F.</au><au>Rifaut, A.</au><aucorp>Philips Research Lab., B-1170 Brussels</aucorp><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A knowledge representation language for requirements engineering</atitle><jtitle>Proc. IEEE; (United States)</jtitle><stitle>JPROC</stitle><date>1986-10-01</date><risdate>1986</risdate><volume>74</volume><issue>10</issue><spage>1431</spage><epage>1444</epage><pages>1431-1444</pages><issn>0018-9219</issn><eissn>1558-2256</eissn><coden>IEEPAD</coden><abstract>Requirements engineering, the phase of software development where the users' needs are investigated, is more and more shifting its concern from the target system towards its environment. A new generation of languages is needed to support the definition of application domain knowledge and the behavior of the universe around the computer. This paper assesses the applicability of classical knowledge representation techniques to this purpose. Requirements engineers insist, however, more on natural representation, whereas expert systems designers insist on efficient automatic use of the knowledge. Given this priority of expressiveness, two candidates emerge: the semantic networks and the techniques based on logic. They are combined in a language called the ERAE model, which is illustrated on examples, and compared to other requirements engineering languages.</abstract><cop>New York, NY</cop><pub>IEEE</pub><doi>10.1109/PROC.1986.13644</doi><tpages>14</tpages></addata></record> |
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subjects | 990210 - Supercomputers- (1987-1989) Application software Applied sciences ARTIFICIAL INTELLIGENCE Computer science control theory systems Design engineering Elevators ENGINEERING Exact sciences and technology EXPERT SYSTEMS GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE HUMAN FACTORS ENGINEERING KNOWLEDGE BASE Knowledge engineering Knowledge representation Learning and adaptive systems Logic MATHEMATICAL LOGIC NATURAL LANGUAGE Programming PROGRAMMING LANGUAGES Software systems |
title | A knowledge representation language for requirements engineering |
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