In testing of software and Internet of Things (IoT) systems, one of necessary type of tests has to verify the consistency of data that are processed and stored in the system. The Data Cycle Test technique can effectively do such tests. The goal of this technique is to verify that the system processes data entities in a system under test in a correct way and that they remain in a consistent state after operations such as create, read, update and delete. Create, read, update and delete (CRUD) matrices are used for this purpose. In this paper, we propose an extension of the Data Cycle Test design technique, which is described in the TMap methodology and related literature. This extension includes a more exact definition of the test coverage, a reflection of the relationships between the tested data entities, an exact algorithm to select and combine read and update operations in test cases for a particular data entity, and verification of the consistency of the produced test cases. As verified by our experiments, in comparison to the original Data Cycle Test technique, this proposed extension helps test designers to produce more consistent test cases that reduce the number of undetected potential data consistency defects.

中文翻译：

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使用CRUD矩阵作为基础模型的动态数据一致性测试

在测试软件和物联网（IoT）系统时，一种必要的测试类型必须验证系统中处理和存储的数据的一致性。数据周期测试技术可以有效地进行此类测试。该技术的目标是验证系统以正确的方式处理被测系统中的数据实体，并且在执行诸如创建，读取，更新和删除之类的操作后，它们保持一致状态。创建，读取，更新和删除（CRUD）矩阵用于此目的。在本文中，我们提出了数据循环测试设计技术的扩展，在TMap方法和相关文献中对此进行了描述。此扩展包括对测试覆盖率的更精确定义，反映了被测数据实体之间的关系，一种精确的算法，用于选择和组合针对特定数据实体的测试用例中的读取和更新操作，并验证产生的测试用例的一致性。经我们的实验验证，与原始数据周期测试技术相比，此提议的扩展有助于测试设计人员生成更一致的测试用例，从而减少未检测到的潜在数据一致性缺陷的数量。