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Test case generation, selection and coverage from natural language

机译:从自然语言中生成测试用例,选择和覆盖

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In Model-based Testing (MBT), test cases are automatically generated from a formal model of the system. A disadvantage of MBT is that developers must deal with formal notations. This limitation is addressed in this paper, where use cases are used to model the system. In previous work, we have proposed an automatic strategy for generating test cases from use cases written in a Controlled Natural Language (CNL), which is an English textual notation with a well-defined grammar. Due to its precise syntax, it can be processed and translated into a formal representation for the purpose of automatic test case generation. This paper extends our previous work by proposing a state-based CNL for describing use case control flows enriched with state and data operations. We translate state-based use case descriptions into CSP processes from which test cases can be automatically generated. In addition, we show how a similar notation can be used to specify test selection via the definition of state-based test purposes, which are also translated into CSP processes. Test generation and selection are mechanised by refinement checking using the CSP tool FDR. Despite the fact that we work at a purely process algebraic level to define a test generation strategy, we are able to address model coverage criteria. Particularly, by using FDR, it is possible to have access to the underlying LTS models; we then implemented algorithms for covering events or transitions, possibly combined with selection using test purposes. We also discuss several ways of improving the efficiency of the test generation strategy. As far as we are aware, this integration between an algebraic approach to test case generation with an operational approach for coverage criteria is an original and promising insight. All steps of the strategy are integrated into a tool that provides a GUI for authoring use cases and test purposes described in the proposed CNL, so the formal CSP notation is completely hidden from the test designer. We illustrate our tool and techniques with a running example and a more elaborate case study taken from an industrial setting. (C) 2019 Elsevier B.V. All rights reserved.
机译:在基于模型的测试(MBT)中,测试用例是根据系统的正式模型自动生成的。 MBT的缺点是开发人员必须处理正式的符号。本文使用用例对系统进行建模,解决了此限制。在先前的工作中,我们提出了一种自动策略,该策略可以从以受控自然语言(CNL)编写的用例中生成测试用例,该用例是具有明确定义的语法的英语文字符号。由于其精确的语法,可以对其进行处理并将其转换为正式的表示形式,以用于自动生成测试用例。本文通过提出基于状态的CNL来描述我们的工作,该CNL描述了用例状态流丰富了状态和数据操作的流程。我们将基于状态的用例描述转换为可自动生成测试用例的CSP流程。另外,我们展示了如何通过基于状态的测试目的的定义,使用类似的符号来指定测试选择,这些状态也被转换为CSP流程。通过使用CSP工具FDR进行细化检查,可以自动生成和选择测试。尽管我们实际上是在纯过程代数层次上定义测试生成策略,但是我们仍然能够满足模型覆盖标准。特别是,通过使用FDR,可以访问基础的LTS模型。然后,我们实现了用于覆盖事件或过渡的算法,并可能结合了出于测试目的的选择。我们还将讨论提高测试生成策略效率的几种方法。据我们所知,用于生成测试用例的代数方法与用于覆盖标准的可操作方法之间的这种集成是一种原始而有希望的见解。该策略的所有步骤都集成到一个工具中,该工具提供了一个GUI,用于编写拟议的CNL中描述的用例和测试目的,因此正式的CSP表示法对测试设计人员完全隐藏。我们通过一个正在运行的示例以及一个来自工业环境的更详尽的案例研究来说明我们的工具和技术。 (C)2019 Elsevier B.V.保留所有权利。

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