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Towards Automated Boundary Value Testing with Program Derivatives and Search

机译:借助程序衍生工具和搜索实现自动边界值测试

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A natural and often used strategy when testing software is to use input values at boundaries, i.e. where behavior is expected to change the most, an approach often called boundary value testing or analysis (BVA). Even though this has been a key testing idea for long it has been hard to clearly define and formalize. Consequently, it has also been hard to automate. In this research note we propose one such formalization of BVA by, in a similar way as to how the derivative of a function is defined in mathematics, considering (software) program derivatives. Critical to our definition is the notion of distance between inputs and outputs which we can formalize and then quantify based on ideas from Information theory. However, for our (black-box) approach to be practical one must search for test inputs with specific properties. Coupling it with search-based software engineering is thus required and we discuss how program derivatives can be used as and within fitness functions. This brief note does not allow a deeper, empirical investigation but we use a simple illustrative example throughout to introduce the main ideas. By combining program derivatives with search, we thus propose a practical as well as theoretically interesting technique for automated boundary value (analysis and) testing.
机译:当测试软件要在边界处使用输入值时,即行为预期变化最大的地方,这是一种自然且经常使用的策略,这种方法通常称为边界值测试或分析(BVA)。尽管长期以来,这一直是关键的测试想法,但仍很难明确定义和形式化。因此,也很难实现自动化。在此研究报告中,我们通过一种类似的方式(考虑到(软件)程序的导数),提出了一种BVA的形式化方法,类似于在数学中如何定义函数的导数。对我们的定义至关重要的是输入和输出之间的距离的概念,我们可以根据信息论的思想对其进行形式化然后进行量化。但是,为了使我们的(黑盒)方法切实可行,必须搜索具有特定属性的测试输入。因此需要将其与基于搜索的软件工程相结合,并且我们讨论了如何将程序派生用作适应度函数并在适应度函数内使用。本简要说明不允许进行更深入的实证研究,但我们在全文中使用一个简单的示例性例子介绍主要思想。通过将程序派生与搜索结合起来,我们提出了一种实用的以及理论上有趣的技术来进行自动边界值(分析和)测试。

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