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实现更佳数据管理测试能力的四项关键

木马童年 2020-10-18 14:39 12 0

从定义角度来看,测试数据实际上是在对应用中的部分信息进行测试。测试数据由名称、账户数量、地址等元素构成,选择正确的数据对于实现成功且全面的测试结果非常关键。选择的数据越全面,测试结果就越具备指导意义。 ...

实现更佳数据管理测试能力的四项关键

从定义角度来看,测试数据实际上是在对应用中的部分信息进行测试。测试数据由名称、账户数量、地址等元素构成,选择正确的数据对于实现成功且全面的测试结果非常关键。选择的数据越全面,测试结果就越具备指导意义。在今天的文章中,我们将共同探讨数据管理测试中的四项重要原则:

1. 发现并分析测试数据

Key #1: Discover and Analyze Test Data

The first task in having a test data management plan is to do an inventory of the data you have on hand. You’re almost certain to have data scattered across multiple systems and in different formats. You should identify the data needed based on your test cases. This really means you must use a toolthat considers the end-to-end business requirements of an application and can link the right data to those tests. Manually locating test data is a time-consuming and error-prone process. A test data management solution that provides complex coverage analysis and data visualization is a better approach.

2. 保护敏感数据

Key #2: Protect Sensitive Data

Comprehensive testing of applications requires the use of real data. This data is culled from production databases and then masked to help secure sensitive parts of the data. Ongoing and new regulations such as GDPR are raising the bar on protecting sensitive data, especially when it’s being used in testing environments. But having clean test data is not enough. You need to have inconsistent data to test for anomalies that are sure to occur with end users. Other approaches to building test data, such as synthetic data creation, should be used when gathering, securing, and consuming test data. Complex data can be created and simultaneously fed into multiple database types, including mainframe platforms.

3. 根据需求交付测试数据

Key #3: Deliver Test Data on Demand

Your data must be built for reusability. Data that can be shared from a central repository will maximize the value of work already done and will allow for new data to be built upon existing components. Data sets can be stored as reusable assets from a central repository and then provisioned to multiple test teams on demand. As the data is provisioned, it is cloned and fully versioned, allowing test teams to work from multiple versions in parallel. Bottlenecks are removed, and testers no longer waste time waiting for data or creating it by hand. They can request and receive test data in minutes using a web-based portal.

4. 实现流程自动化

Key #4: Automate the Process

What if you could automate the entire processes of scripting, data masking, data generation, cloning, and provisioning? The world would indeed be a better place. With CA Test Data Manager and CA Agile Requirements Designer, you can move your teams closer to testing nirvana. Once the test data has been linked to specific tests, the tests can be fed directly into automated testing tools like CA Application Test and lifecycle management tools such as CA Agile Central. This stabilized automation framework guarantees that data will be provisioned in the right state when needed by your testers. Additionally, when test cases and data are linked, they become traceable to the requirements. When requirements change, the data can be updated automatically.

数据管理 敏感数据
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