使用可变性语言对软件即服务配置进行自动化测试

Sachin Patel, Vipul Shah
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引用次数: 4

摘要

云技术提供的好处迫使企业采用软件即服务(SaaS)模型来满足其企业软件需求。必须对SaaS进行配置或定制,以满足订阅它的每个企业的特定需求。IT服务提供商必须处理测试为不同企业创建的许多此类配置的问题。软件需要定期升级,并且需要持续测试配置,以确保业务连续性。为了有效地运行测试组织,测试周期的自动化是必要的。为大量配置开发自动化测试脚本是一项重要的任务,因为它们之间的差异可能从少量用户界面更改到业务流程级别更改不等。我们提出了一种结合模型驱动工程和可变性建模的优点来解决这个问题的方法。该方法由企业软件测试建模语言组成,用于对测试用例进行建模。我们使用Common Variability Language对测试用例中的可变性进行建模,并在基本模型上应用模型转换,为每个配置生成一个测试模型。这些模型用于为所有配置生成自动化的测试脚本。我们描述了测试建模语言和一个实验,表明该方法可以用于自动生成自动化测试脚本中的变量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automated testing of software-as-a-service configurations using a variability language
The benefits offered by cloud technologies have compelled enterprises to adopt the Software-as-a-Service (SaaS) model for their enterprise software needs. A SaaS has to be configured or customized to suit the specific requirements of every enterprise that subscribes to it. IT service providers have to deal with the problem of testing many such configurations created for different enterprises. The software gets upgraded periodically and the configurations need to be tested on an ongoing basis to ensure business continuity. In order to run the testing organization efficiently, it is imperative that the test cycle is automated. Developing automated test scripts for a large number of configurations is a non-trivial task because differences across them may range from a few user interface changes to business process level changes. We propose an approach that combines the benefits of model driven engineering and variability modeling to address this issue. The approach comprises of the Enterprise Software Test Modeling Language to model the test cases. We use the Common Variability Language to model variability in the test cases and apply model transformations on a base model to generate a test model for each configuration. These models are used to generate automated test scripts for all the configurations. We describe the test modelling language and an experiment which shows that the approach can be used to automatically generate variations in automated test scripts.
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