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Automated Software Engineering

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01.05.2024

Using data mining techniques to generate test cases from graph transformation systems specifications

verfasst von: Maryam Asgari Araghi, Vahid Rafe, Ferhat Khendek

Erschienen in: Automated Software Engineering | Ausgabe 1/2024

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Abstract

Software testing plays a crucial role in enhancing software quality. A significant portion of the time and cost in software development is dedicated to testing. Automation, particularly in generating test cases, can greatly reduce the cost. Model-based testing aims at generating automatically test cases from models. Several model based approaches use model checking tools to automate test case generation. However, this technique faces challenges such as state space explosion and duplication of test cases. This paper introduces a novel solution based on data mining algorithms for systems specified using graph transformation systems. To overcome the aforementioned challenges, the proposed method wisely explores only a portion of the state space based on test objectives. The proposed method is implemented using the GROOVE tool set for model-checking graph transformation systems specifications. Empirical results on widely used case studies in service-oriented architecture as well as a comparison with related state-of-the-art techniques demonstrate the efficiency and superiority of the proposed approach in terms of coverage and test suite size.

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Titel: Using data mining techniques to generate test cases from graph transformation systems specifications
verfasst von: Maryam Asgari Araghi
Vahid Rafe
Ferhat Khendek
Publikationsdatum: 01.05.2024
Verlag: Springer US
Erschienen in: Automated Software Engineering / Ausgabe 1/2024
Print ISSN: 0928-8910
Elektronische ISSN: 1573-7535
DOI: https://doi.org/10.1007/s10515-024-00417-0

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