Graph Transformations

Model based testing is an automated process in which executable test cases are derived from behavioral models of a system. Model checking is another verification approach in which all reachable states of a system are generated. In the literature, there are different approaches which suggest using model checkers for model based test case generation. Since all possible states and paths are generated by the model checker, selecting different paths in the state space as test cases based on some coverage criteria seems a promising solution. However, all these approaches suffer from two main challenges. The first challenge is the state space explosion problem which prevents the model checker to generate all the states. The second one is generating redundant test cases (paths). Recently, methods using meta-heuristic and evolutionary approaches have been proposed to cope with these two problems. Therefore, exploring a portion of the state space to detect the test objectives using an optimization approach can be a proper way to manage the state space explosion and generates the optimal test suites with the least redundancy. In this paper, an approach is proposed using Bayesian optimization algorithm (BOA) to generate test cases for service oriented systems specified through graph transformation. In the proposed approach, test suite is a set of paths on the state space that starting from an initial state and leading to the states in which all the test objectives is satisfied. In this research, we have implemented BOA with three different structures in GROOVE, an open source toolset for designing and model checking graph transformation. Experimental results show that our solution generates better results in terms of coverage, memory usage and speed in different case studies in comparison with the existing approaches.

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

Asgari Araghi,

Rafe,

Khendek

2024

Autom Softw Eng

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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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Graph Transformations

Cited by 14 publications

References 6 publications

Hans-Jörg Kreowski, Renate Klempien-Hinrichs, Sabine Kuske

Hans-Jörg Kreowski, Renate Klempien-Hinrichs, Sabine Kuske

Using Bayesian optimization algorithm for model-based integration testing

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

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