Category-Partition is a functional testing technique that is based on the idea that the input domain of the system under test can be divided into sub-domains, with the assumption that inputs that belong to the same sub-domain trigger a similar behaviour and that therefore it is sufficient to select one input from each sub-domain. Category-Partition proceeds in several steps, from the identification of so-called categories and choices, possibly constrained, which are subsequently used to form test frames, i.e., combinations of choices, and eventually test cases. This paper reports on an ongoing attempt to automate as many of those steps as possible, with graphical-user interface tool support. Specifically, the user interface allows the user to specify parameters as well as so-called environment variables, further specify categories and choices with optional constraints. Choices are provided with precise specifications with operations specific to their types (e.g., Boolean, Integer, Real, String). Then, the tool automates the construction of test frames, which are combinations of choices, according to alternative selection criteria, and the identification of input values for parameters and environment variables for these test frames, thereby producing test cases. The paper illustrates the capabilities of the tool with the use of nine different case studies.

翻译：分类划分是一种功能测试技术，其核心思想在于：被测系统的输入域可被划分为若干子域，并假设属于同一子域的输入会触发相似的系统行为，因此从每个子域中选择一个输入即已足够。分类划分测试包含多个步骤：从识别所谓的类别与（可能带有约束的）选项开始，随后利用这些选项构建测试框架（即选项的组合），最终生成测试用例。本文报告了一项旨在通过图形用户界面工具支持，尽可能自动化上述步骤的持续尝试。具体而言，该用户界面允许用户指定参数及所谓的环境变量，进一步定义类别与可选的约束条件。选项通过针对其类型（如布尔型、整型、实数型、字符串型）的特定操作进行精确描述。随后，工具可根据不同的选择标准自动构建测试框架（即选项的组合），并为这些测试框架中的参数和环境变量识别输入值，从而生成测试用例。本文通过九个不同的案例研究展示了该工具的功能。