论文标题
使用CRUD矩阵作为基础模型进行动态数据一致性测试
Dynamic Data Consistency Tests Using a CRUD Matrix as an Underlying Model
论文作者
论文摘要
在对软件和物联网（IoT）系统的测试中，必要的测试类型之一必须验证已处理和存储在系统中的数据的一致性。数据周期测试技术可以有效地进行此类测试。该技术的目的是验证系统以正确的方式处理正在测试的系统中的数据实体，并在操作之后保持一致的状态，例如创建，读取，更新和删除。创建，读取，更新和删除（CRUD）矩阵用于此目的。在本文中，我们提出了数据周期测试设计技术的扩展，该技术在TMAP方法和相关文献中进行了描述。该扩展名包括对测试覆盖范围的更精确的定义，对测试数据实体之间关系的反映，一种精确的算法，用于选择和组合特定数据实体的测试用例中的读取和更新操作以及对生产测试案例的一致性的验证。通过我们的实验证实，与原始数据周期测试技术相比，该提出的扩展可以帮助测试设计师生成更一致的测试用例，以减少未发现潜在数据一致性缺陷的数量。
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.
