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

ITR：协作研究：新一代可扩展、经济高效的回归测试技术

• 批准号: 0080900
• 负责人: Gregg Rothermel
• 金额: $ 22.47万
• 依托单位: Oregon State University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2000
• 资助国家: 美国
• 起止时间: 2000-09-01 至 2004-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0080900&HistoricalAwards=false
• 关键词: ITR; Collaborative; Research; New; Generation

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.

Ccr-0080900 PI：Rothermel，格雷格俄勒冈州立大学ITR：SW：协作研究：新一代可扩展、经济高效的回归测试技术协作PI：Sebastian Elbaum(ITR-0080898)此项目是与内布拉斯加州-林肯大学的Sebastian Elbaum(CCR-0080898)合作进行的。回归测试是在修改后的软件上执行的一种昂贵的过程，以确保修改不会损害其质量。为了帮助这一过程，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，但它们在几个方面仍然有限。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性，并且错误的可能性在程序的各个部分是恒定的。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。这项研究将提供：(1)捕捉必要因素的全面回归测试成本模型；(2)考虑这些因素的回归测试技术；(3)更准确地了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；以及(4)帮助软件工程师选择和创建成本效益高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，这项研究还包括大量的经验部分，并将提供关于技术和因素的公开的经验数据基础。总而言之，这些贡献将支持更高效和有效的回归测试，并提高软件质量。