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Test Case Generation From Web Usage Information

Title
Test Case Generation From Web Usage Information
Type
Article in International Conference Proceedings Book
Year
2021
Authors
Jorge Esparteiro Garcia
(Author)
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Ana C. R. Paiva
(Author)
FEUP
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Anca-Maria Bizoi
(Author)
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Conference proceedings International
Pages: 913-920
International Conference on ENTERprise Information Systems (CENTERIS) / International Conference on Project MANagement (ProjMAN) / International Conference on Health and Social Care Information Systems and Technologies (HCist)
Vilamoura, PORTUGAL, OCT 21-23, 2020
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Authenticus ID: P-00T-KEB
Resumo (PT):
Abstract (EN): In the context of SaaS (Software as a Service) where software has to be up and miming 7 days a week and 24 hours a day, keeping the requirements specification and related test cases up to date can be difficult. Managing requirements in this context has additional challenges that need to be taken into account, for instance, re-prioritize requirements continuously and identify/update new dependencies among them. When requirements change, related test cases need to be updated accordingly. We claim that extracting and analyzing the usage of the SaaS can help to maintain requirements and test cases updated and contribute to improve the overall quality of the services provided. This paper presents an extension to REQAnalytics. REQAnalytics is a recommendation system that collects information about the usage of a SaaS and generates recommendations to improve the SaaS provided. The evolution involves extending the analysis performed over the sequences of functionalities (requirements) and refining the data provided for Software Requirements Specification, with the purpose of helping the requirements engineers in the requirement maintenance activities, and to improve the overall quality of the services. Furthermore, the extension presented in this paper is able to generate test cases in a regression testing context. (C) 2021 The Authors. Published by Elsevier B.V.
Language: English
Type (Professor's evaluation): Scientific
No. of pages: 8
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