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CiRA: An Open-Source Python Package for Automated Generation of Test Case Descriptions from Natural Language Requirements
Blekinge Institute of Technology, Faculty of Computing, Department of Software Engineering.ORCID iD: 0000-0003-3995-6125
Netlight Consulting GmbH and Fortiss GmbH, Germany.
Blekinge Institute of Technology, Faculty of Computing, Department of Software Engineering.ORCID iD: 0000-0002-2916-4020
2023 (English)In: Proceedings - 31st IEEE International Requirements Engineering Conference Workshops, REW 2023 / [ed] Schneider K., Dalpiaz F., Horkoff J., Institute of Electrical and Electronics Engineers (IEEE), 2023, p. 68-71Conference paper, Published paper (Refereed)
Abstract [en]

Deriving acceptance tests from high-level, natural language requirements that achieve full coverage is a major manual challenge at the interface between requirements engineering and testing. Conditional requirements (e.g., 'If A or B then C.') imply causal relationships which - when extracted - allow to generate these acceptance tests automatically. This paper presents a tool from the CiRA (Causality In Requirements Artifacts) initiative, which automatically processes conditional natural language requirements and generates a minimal set of test case descriptions achieving full coverage. We evaluate the tool on a publicly available data set of 61 requirements from the requirements specification of the German Corona-Warn-App. The tool infers the correct test variables in 84.5% and correct variable configurations in 92.3% of all cases, which corroborates the feasibility of our approach. © 2023 IEEE.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2023. p. 68-71
Keywords [en]
acceptance test, BERT, natural language processing, requirements engineering, test case description, Computer software selection and evaluation, High level languages, Natural language processing systems, Open source software, Open systems, Case description, Language processing, Natural language requirements, Natural languages, Open-source, Requirement engineering, Test case, Acceptance tests
National Category
Software Engineering
Identifiers
URN: urn:nbn:se:bth-25557DOI: 10.1109/REW57809.2023.00019ISI: 001085223300015Scopus ID: 2-s2.0-85174681463ISBN: 9798350326918 (print)OAI: oai:DiVA.org:bth-25557DiVA, id: diva2:1810132
Conference
31st IEEE International Requirements Engineering Conference Workshops, REW 2023, Hannover, 4 Sept - 8 Sept 2023
Part of project
SERT- Software Engineering ReThought, Knowledge Foundation
Funder
Knowledge Foundation, 20180010Available from: 2023-11-07 Created: 2023-11-07 Last updated: 2024-01-02Bibliographically approved

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Frattini, JulianBauer, Andreas

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