Whereas the current dominant paradigm treats testing as a phase that precedes delivery, we will build the foundation for treating analysis and testing as on-going activities to improve quality assurance without pause through several generations of product, in the deployed environment as well as the development environment. Software in the deployed environment will be monitored not only to check conformance to required properties but also to validate and refine the models andassumptions on which quality assurance activities in the development environment depend. The degree of monitoring and transmission of information to the development environment will differ depending on performance and security requirements of the end-user and will always be under user control. Approach The perpetual testing project is a collaboration of researchers at the University of Massachusetts, Amherst, the University of California at Irvine, and Purdue University. The primary foci of the University of Massachusetts effort are on improving static analysis technology and tools, on integrating static and dynamic analysis techniques, and on developing process technologies and artifacts.
Perpetual testing is necessarily incremental.
Analysis and testing processes are carried out in response to changes in software artifacts or available information or in anticipation of change. Improvements to these technologies will focus largely on scalability and incrementality for large evolving systems. Analysis and testing will be aimed at attaining and maintaining adequate adherence of all software artifacts to relations captured by a rich web of hypercode links, including dependence relations among software components and among properties and analysis techniques. To enhance cost-effective perpetual testing of evolving systems, UMass will explore incremental and evolutionary techniques for static analysis. UMass will deliver static analysis tools that employ interprocedural summarization techniques for sequential, concurrent, and distributed systems and thereby support scalability.