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

CCR-0080898 PI：塞巴斯蒂安埃尔鲍姆 内布拉斯加大学林肯分校ITR：SW：协作研究：新一代可扩展的， 经济高效的回归测试技术 合作PI：Gregg Rothermel（CCR-0080900）该项目是与俄勒冈州州立大学的Gregg Rothermel（CCR-0080900）合作进行的。回归测试是对修改后的软件执行的一个昂贵的过程，以提供修改不会损害其质量的信心。 为了帮助这个过程，以前的研究已经考虑了各种测试套件重用技术。 尽管这些技术取得了进展，但它们在沿着几个维度上仍然受到限制。 例如，他们通常假设测试用例具有相等的成本，故障具有相等的严重性，并且故障可能性在程序的各个部分中是恒定的。 这些假设在实践中是不现实的，并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。 该研究将提供：（1）全面的回归测试成本模型，它捕获了必要的因素;（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成本有效的回归测试工具和过程的指南。 除了提供模型，算法和流程外，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经验数据的公开基础。 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-0080898 PI: Sebastian Elbaum Univ. of Nebraska - Lincoln ITR:SW: Collaborative Research: A New Generation of Scalable, Cost-Effective Regression Testing Techniques Collaborating PI: Gregg Rothermel (CCR-0080900)This project is carried out in collaboration with Gregg Rothermel (CCR-0080900)of Oregon State University. 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.