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Investigating the Use of Model-Based Method for Improving the Quality of Natural Language Requirements: A Controlled Empirical Study

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dc.contributor.author Gupta, Munmun
dc.description.abstract Requirement engineering is a critical phase in software development that describes the customer needs and specifications for the software. Requirements are gathered through various sources and documented for a software product to be developed, written in Natural Language (NL). NL requirements are fault prone because they can be interpreted in different ways due its inherent imprecision, ambiguity, and vagueness. To address these problems, model-based requirements verification method called NLtoSTD (State Transition Diagram) is proposed. This paper evaluates the ability of NLtoSTD method in detecting faults when used on NL requirements and to improve its cognitive friendliness to the stakeholders. Motivated by the earlier study, we revised our proposed method and performed an empirical study. The participants employed the NLtoSTD method to inspect documents to identify ambiguities, incompleteness and inconsistencies. The experiment result shows an improvement over the previous results that the NLtoSTD is a method for verification of NL requirements. en_US
dc.title Investigating the Use of Model-Based Method for Improving the Quality of Natural Language Requirements: A Controlled Empirical Study en_US
dc.date.accessioned 2014-04-14T18:30:22Z
dc.date.available 2014-04-14T18:30:22Z
dc.date.issued 2014-04-14
dc.identifier.uri http://hdl.handle.net/10365/23141
dc.date 2014 en_US
dc.thesis.degree Master of Science. en_US
dc.contributor.advisor Walia, Gursimran
dc.subject.course Master of Science / Software Engineering, College of Science and Mathematics, 2014. en_US

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