Scalable Program-Analysis-Based Testing and Maintenance: Infrastructure and Experimentation

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Maintenance and testing of software are expensive. Program analysis techniques, which analyze source code to obtain information about software, promise to reduce this expense by providing information that helps software engineers perform specific maintenance and testing tasks such as program understanding, impact analysis, and regression testing. However, to be adopted or even considered for adoption, program-analysis-based testing and maintenance techniques must be empirically demonstrated to scale to large software systems. The primary goal of this reqearch is to empirically investigate the applicability of program- analysis-based testing and maintenance techniques to large- scale systems. The research involves three overall efforts: (1) construction of an extensible experimental infrastructure including a software system and repository of subject systems; (2) development of program-analysis techniques that support testing and maintenance of large- scale systems; (3) rigorous empirical evaluation of the infrastructure, and of the program-analysis-based testing and maintenance techniques. The principal results expected from this work are an improved understanding of, and improved techniques for, program-analysis-based testing and maintenance -- founded on hard empirical data. The work will also provide a publicly available infrastructure, that will support future tool development for, experimentation with, and education in program-analysis- based testing and maintenance techniques throughout the software engineering community.