面向循证的可测试性测量
Towards Evidence-based Testability Measurements
摘要：
评估软件的可测试性可以帮助软件管理者优化测试预算和识别重构的机会。在本文中，我们放弃了传统的基于软件度量和在过去的项目中观察到的测试特征之间的相关性来追求可测试性度量的方法，例如，测试用例的大小、组织或代码覆盖率。我们提出了一种全新的方法，利用自动测试生成和突变分析，以量化的证据量的相对硬度，确定有效的测试用例。我们介绍了两种新的基于证据的可测试性指标，描述了一个原型来计算它们，并讨论了我们的测量是否可以反映实际的可测试性问题的初步研究结果。
英文摘要：
Evaluating Software testability can assist software managers in optimizing testing budgets and identifying opportunities for refactoring. In this paper, we abandon the traditional approach of pursuing testability measurements based on the correlation between software metrics and test characteristics observed on past projects, e.g., the size, the organization or the code coverage of the test cases. We propose a radically new approach that exploits automatic test generation and mutation analysis to quantify the amount of evidence about the relative hardness of identifying effective test cases. We introduce two novel evidence-based testability metrics, describe a prototype to compute them, and discuss initial findings on whether our measurements can reflect actual testability issues.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
