A Framework for the Regression Testing of Model-to-Model Transformations

Issam Al-Azzoni, S. Iqbal
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Abstract

Background: Model transformations play a key role in Model-Driven Engineering (MDE). Testing model transformation is an important activity to ensure the quality and correctness of the generated models. However, during the evolution and maintenance of these model transformation programs, frequently testing them by running a large number of test cases can be costly. Regression test selection is a form of testing, which selects tests from an existing test suite to test a modified program. Aim: The aim of the paper is to present a test selection approach for the regression testing of model transformations. The selected test case suite should be smaller in size than the full test suite, thereby reducing the testing overhead, while at the same time the fault detection capability of the full test suite should not be compromised. Method: approach is based on the use of a traceability mapping of test cases with their corresponding rules to select the affected test items. The approach is complemented with a tool that automates the proposed process. Results: Our experiments show that the proposed approach succeeds in reducing the size of the selected test case suite, and hence its execution time, while not compromising the fault detection capability of the full test suite. Conclusion: The experimental results confirm that our regression test selection approach is cost-effective compared to a retest strategy.
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模型到模型转换的回归测试框架
背景:模型转换在模型驱动工程(MDE)中起着关键作用。测试模型转换是保证生成模型质量和正确性的一项重要活动。然而,在这些模型转换程序的发展和维护过程中,通过运行大量的测试用例来频繁地测试它们是非常昂贵的。回归测试选择是一种测试形式,它从现有的测试套件中选择测试来测试修改后的程序。目的:本文的目的是提出一种模型转换回归检验的测试选择方法。所选择的测试用例套件应该比完整的测试套件更小,从而减少测试开销,同时完整测试套件的故障检测能力不应该受到损害。方法:方法是基于使用测试用例的可追溯性映射及其相应的规则来选择受影响的测试项。该方法还配有一个工具,可以使所建议的过程自动化。结果:我们的实验表明,所提出的方法成功地减少了所选测试用例套件的大小,从而减少了它的执行时间,同时不影响整个测试套件的故障检测能力。结论:与重测策略相比,我们的回归测试选择方法具有较高的成本效益。
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