2006
Conference article
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A new quality model for natural language requirements specifications
Berry D M, Bucchiarone A, Gnesi S, Lami G, Trentanni GThis paper describes an extension to the natural language requirements specification quality model that is the basis for the QuARS (Quality Analyzer of Requirements Specification) tool. The extension takes into account ambiguitiesthat were not handled before.
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CNR IRIS
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2003
Software
Metadata Only Access
QuARS: Quality Analyzer for Requirement Specifications
Fabbrini F, Fusani M, Gnesi S, Lami G, Trentanni GThe tool QuARS (Quality Analyzer for Requirement Specifications) is based on a quality model composed of a set of high-level quality properties for NL requirements to be evaluated by means of syntactic and structural indicators directly detectable and measurable looking at the sentences in requirement document. This quality model, even though not exhaustive, is sufficiently specific to include a significant part of the lexical and syntax-related issues of requirement documents. QuARS receives as input a text document and provides the user with the indication of those sentences of the document that, according to the quality model, have to be considered as defective.
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CNR IRIS
2005
Conference article
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Quality analysis of NL requirements: an industrial case study
Bucchiarone A, Gnesi SNowadays common practice indicates that the Requirement Engineering (RE) process critically influences the success of the system development life cycle. Several commercial tools allow to classify, archive and manage requirements and then to print out reports and requirement documents. QuARS (Quality Analyzer for Requirements Specifications) is an automatic analyzer of such requirement documents, developed by ISTI - CNR, that can be adopted to evaluate the document quality by linguistic point of view. In this paper is presented how a requirement management tool, an automatic document generator and QuARS can be integrated to define an RE automation support. The case study investigates and highlights the efficacy and the role of such proposed support in the Siemens C.N.X. development process.
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CNR IRIS
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2001
Conference article
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The linguistic approach to the natural language requirements quality: benefit of the use of an automatic tool
Fabbrini F, Fusani M, Gnesi S, Lami GNatural Language (NL) requirements are widely used in software industry, at least as the first level of description of a system. Unfortunately they are often prone to errors and this is partially caused by interpretation problems due to the use of NL itself. This paper presents a methodology for the analysis of natural language requirements based on a quality model addressing a relevant part of the interpretation problems that can be approached at linguistic level. To provide an automatic support to this methodology a tool called QuARS (Quality Analyzer of Requirement Specification) has been implemented. The methodology and the underlying quality model have been validated by analyzing with QuARS several industrial software NL requirement documents showing interesting results.
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CNR IRIS
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2005
Journal article
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An Automatic Tool for the Analysis of Natural Language Requirements
Lami G, Gnesi S, Trentanni G, Fabbrini F, Fusani MUsing automatic tools for the quality analysis of Natural Language (NL) requirements is recognized as a key factor for achieving software quality. Unfortunately few tools and techniques for the NL requirements analysis are currently available. This paper presents a methodology and a tool (called QuARS - Quality Analyzer for Requirement Specifications) for analyzing NL requirements in a systematic and automatic way. QuARS allows requirements engineers to perform an initial parsing of the requirements in order to automatically detect potential linguistic defects that could cause interpretation problems at subsequent stages in developing the software. This tool is also able to partially support the consistency and completeness analysis by clustering the requirements according to specific topics.Source: COMPUTER SYSTEMS SCIENCE AND ENGINEERING, vol. 20 (issue 1), pp. 53-62
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CNR IRIS
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