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Automatic analysis of requirements consistency with the B method

Published: 27 March 2010 Publication History

Abstract

A consistent requirements specification is a fundamental success factor for quality software development projects. On the one hand, writing requirements in a natural language is not good for an automated conflict detection process. On the other hand, formal methods provide the basis for consistency checking of requirements specification automatically. In this paper, the potential of the B method for improving the requirements quality under the consistency dimension is discussed. We present an approach to use B specifications derived from a controlled natural language to identify requirements inconsistencies

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Cited By

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  • (2022)Automatic Transformation of Natural to Unified Modeling Language: A Systematic Review2022 IEEE/ACIS 20th International Conference on Software Engineering Research, Management and Applications (SERA)10.1109/SERA54885.2022.9806783(112-119)Online publication date: 25-May-2022
  • (2020)Application of machine learning techniques to the flexible assessment and improvement of requirements qualitySoftware Quality Journal10.1007/s11219-020-09511-428:4(1645-1674)Online publication date: 27-Apr-2020
  • (2020)A systemic framework for crowdsourced test report quality assessmentEmpirical Software Engineering10.1007/s10664-019-09793-825:2(1382-1418)Online publication date: 27-Feb-2020
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Published In

cover image ACM SIGSOFT Software Engineering Notes
ACM SIGSOFT Software Engineering Notes  Volume 35, Issue 2
March 2010
113 pages
ISSN:0163-5948
DOI:10.1145/1734103
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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 27 March 2010
Published in SIGSOFT Volume 35, Issue 2

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Author Tags

  1. B method
  2. consistency checking
  3. formal requirement specification
  4. requirement analysis

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View all
  • (2022)Automatic Transformation of Natural to Unified Modeling Language: A Systematic Review2022 IEEE/ACIS 20th International Conference on Software Engineering Research, Management and Applications (SERA)10.1109/SERA54885.2022.9806783(112-119)Online publication date: 25-May-2022
  • (2020)Application of machine learning techniques to the flexible assessment and improvement of requirements qualitySoftware Quality Journal10.1007/s11219-020-09511-428:4(1645-1674)Online publication date: 27-Apr-2020
  • (2020)A systemic framework for crowdsourced test report quality assessmentEmpirical Software Engineering10.1007/s10664-019-09793-825:2(1382-1418)Online publication date: 27-Feb-2020
  • (2019)Detecting Non-Atomic Requirements in Software Requirements Specifications Using Classification Methods2019 1st International Conference on Cybernetics and Intelligent System (ICORIS)10.1109/ICORIS.2019.8874888(269-273)Online publication date: Aug-2019
  • (2018)Automated quality assessment for crowdsourced test reports of mobile applications2018 IEEE 25th International Conference on Software Analysis, Evolution and Reengineering (SANER)10.1109/SANER.2018.8330224(368-379)Online publication date: Mar-2018
  • (2015)A methodology for the classification of quality of requirements using machine learning techniquesInformation and Software Technology10.1016/j.infsof.2015.07.00667:C(180-195)Online publication date: 1-Nov-2015
  • (2014)Transforming natural language into controlled language in requirements elicitation: a pre-conceptual-schema-based conceptual synthesisRevista Facultad de Ingeniería Universidad de Antioquia10.17533/udea.redin.18657(132-145)Online publication date: 27-Feb-2014
  • (2012)An ontological pivot model to interoperate heterogeneous user requirementsProceedings of the 5th international conference on Leveraging Applications of Formal Methods, Verification and Validation: applications and case studies - Volume Part II10.1007/978-3-642-34032-1_35(344-358)Online publication date: 15-Oct-2012
  • (2012)Using UML stereotypes to support the requirement engineeringProceedings of the 12th international conference on Computational Science and Its Applications - Volume Part IV10.1007/978-3-642-31128-4_5(51-66)Online publication date: 18-Jun-2012

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