CAREER: Configuration-Aware Testing Through Intelligent Sampling to Improve Software Dependability

职业：通过智能采样进行配置感知测试以提高软件可靠性

• 批准号: 0747009
• 负责人: Myra Cohen
• 金额: $ 40万
• 依托单位: University of Nebraska-Lincoln
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-02-15 至 2014-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0747009&HistoricalAwards=false
• 关键词: CAREER; Configuration; Aware; Testing; Through

Proposal Number: CCF-0747009TITLE: CAREER: Configuration-Aware Testing Through Intelligent Sampling to Improve Software DependabilityPI: Myra B. CohenThe advent of modern software systems and the rise of system configurability add a new dimension of complexity to the task of ensuring system quality. A single configurable software system encapsulates thousands or millions of unique program configurations or instantiations, and each configuration may behave differently under the same software test sequences acting as a unique program from the tester?s point of view. Testing techniques should not assume configuration heterogeneity, but should instead sample a representative set of program instantiations. This project focuses on the configuration-definition layer (CDL) of software to develop a set of scalable and adaptive configuration-aware testing techniques. It leverages research from combinatorial interaction testing for sampling, and work in satisfiability solving to handle complex dependencies. Specifically, it creates new algorithmic techniques to sample test configurations, creates models for cost-based sampling in time-constrained or risk-based environments, and explores several domain specific customizations. The impact of this work is that it explores a new avenue of research for software testers that focuses on the CDL, while providing theoretical results of interest to a broader community. It includes a tightly woven educational plan that involves both graduate and undergraduate students.

提案编号：CCF-0747009标题：职业生涯：通过智能采样进行验证感知测试以提高软件可靠性PI：Myra B。Cohen现代软件系统的出现和系统可配置性的兴起为确保系统质量的任务增加了新的复杂性。单个可配置软件系统封装了数千或数百万个独特的程序配置或实例，并且每个配置在相同的软件测试序列下可能表现不同，作为测试仪的独特程序？的观点。测试技术不应该假设配置异构性，而应该对一组有代表性的程序实例进行采样。 本计画针对软体的组态定义层（CDL），发展一套可扩充且具适应性的组态感知测试技术。 它利用组合交互测试的研究进行采样，并在满足性解决中工作以处理复杂的依赖关系。 具体来说，它创建了新的算法技术来对测试配置进行采样，创建了在时间受限或基于风险的环境中基于成本的采样模型，并探索了几个特定领域的定制。这项工作的影响在于，它为软件测试人员探索了一条新的研究途径，重点是CDL，同时为更广泛的社区提供了感兴趣的理论结果。 它包括一个紧密编织的教育计划，涉及研究生和本科生。