ITR: Collaborative Research: A New Generation of Scalable, Cost-Effective Regression Testing Techniques

项目负责人：Rothermel， Gregg俄勒冈州立大学ITR:SW：合作研究：新一代可扩展的，具有成本效益的回归测试技术合作负责人：Sebastian Elbaum （ITR-0080898）本项目由内布拉斯加州大学林肯分校的Sebastian Elbaum （CCR-0080898）合作完成。回归测试是在修改后的软件上执行的一个昂贵的过程，以提供修改没有损害其质量的信心。为了帮助这个过程，以前的研究考虑了各种测试套件重用技术。尽管这些技术取得了进步，但它们在几个方面仍然受到限制。例如，他们通常假设测试用例具有相同的成本，错误具有相同的严重程度，并且错误的可能性在程序的各个部分之间是恒定的。这些假设在实践中是不现实的，并且限制了技术的适用性和有效性。拟议的研究将解决这些限制。本研究将提供：(1)综合回归测试成本模型，以捕捉必要的因素；(2)考虑这些因素的回归测试技术；(3)更精确地理解这些因素对回归可测试性、程序和测试设计以及软件工程实践的影响；(4)帮助软件工程师选择和创建经济有效的回归测试工具和过程的指导方针。除了提供模型、算法和过程之外，该研究还包括大量的经验成分，并将提供有关技术和因素的公开可用的经验数据基础。总之，这些贡献将支持更高效和有效的回归测试，并提高软件的质量。

CCR-0080900 PI: Rothermel, Gregg Oregon State University ITR:SW: Collaborative Research: A New Generation of Scalable, Cost-Effective Regression Testing Techniques Collaborating PI: Sebastian Elbaum (ITR-0080898)This project is carried out in collaboration with Sebastian Elbaum (CCR-0080898)of the University of Nebraska - Lincoln. Regression testing is an expensive process performed on modified software to provide confidence that modifications have not impaired its quality. To help with this process, previous research has considered various test-suite reuse techniques. Despite progress with these techniques, they remain limited along several dimensions. For example, they typically assume that test cases have equivalent costs, faults have equivalent severities, and fault likelihood is constant across portions of a program. These assumptions are unrealistic in practice, and limit the applicability and effectiveness of techniques. The proposed research will address these limitations. The research will provide: (1) comprehensive regression testing cost models that capture the necessary factors; (2) regression testing techniques that account for these factors; (3) more precise understanding of the effects these factors have on regression testability, program and test design, and software engineering practice; and(4) guidelines that help software engineers select and create cost-effective regression testing tools and processes. In addition to providing models, algorithms, and processes, the research includes a substantial empirical component, and will provide a publicly available base of empirical data about techniques and factors. Together, these contributions will support more efficient and effective regression testing, and improve the quality of software.