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GUIDiVa: Automated Discovery and Validation of State-Based GUI Invariants

机译:GUIDiVa:基于状态的GUI不变量的自动发现和验证

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Applications with a Graphical User Interface (GUI) front-end are ubiquitous, thus it is of great importance to assure the quality of such systems. Model-based GUI testing provides an effective mechanism for automated testing of applications with a GUI. However, most existing model-based GUI test generation techniques produce many infeasible (i.e., Broken) event sequences which are used as test cases. This happens primarily because they ignore behavioral specifications of the GUI under test. In this paper, we present an automated black box framework that reveals an important set of GUI invariants as state-based event constraints. GUIDiVa, an iterative algorithm at the core of our framework, enumerates all possible constraint violations as potential reasons of a test case failure, on the failed event of the infeasible test case. It further selects and adds the most promising constraints of each iteration to a final set based on our notion of constraint Validity Weight. The results of empirical studies on both seeded and nine non-trivial study subjects show that our framework is capable of capturing important aspects of GUI behavior, while considerably reducing the number of insfeasible test cases. Additionally, a human oracle is used to further validate the accuracy of the discovered constraints.
机译:具有图形用户界面(GUI)前端的应用程序无处不在,因此确保此类系统的质量非常重要。基于模型的GUI测试为使用GUI自动测试应用程序提供了有效的机制。但是,大多数现有的基于模型的GUI测试生成技术都会生成许多不可行的(即Broken)事件序列,用作测试用例。发生这种情况的主要原因是,他们忽略了被测GUI的行为规范。在本文中,我们提出了一个自动化的黑匣子框架,该框架揭示了一组重要的GUI不变量作为基于状态的事件约束。 GUIDiVa是我们框架的核心迭代算法,它在无法通过测试用例的失败事件中,将所有可能的约束违例枚举为导致测试用例失败的潜在原因。它根据我们的约束有效性权重概念进一步选择并将每个迭代的最有希望的约束添加到最终集合中。对有种子的研究对象和9个非重要的研究对象进行的实证研究结果表明,我们的框架能够捕获GUI行为的重要方面,同时大大减少了不可行的测试案例的数量。另外,人工神谕用于进一步验证发现的约束的准确性。

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