Richard T. Mraz

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While Artiicial Intelligence techniques have been applied to a variety of software engineering applications, the area of automated software testing remains largely unexplored. Yet, test cases for certain types of systems (e.g., those with command language interfaces and transaction based systems) are similar to plans. We have exploited this similarity by(More)
As test case automation increases, the volume of tests can become a problem. Further, it may not be immediately obvious whether the test generation tool generates effective test cases. Indeed, it might be useful to have a mechanism that is able to learn, based on past history, which test cases are likely to yield more failures versus those that are not(More)
Domain Models [8, 9, 25] have long been used as a basis for software development and reuse. We present a specialized, simplified domain model that has been used for system testing in industry as the framework for a system testing approach we call Application Domain Based Testing. Sleuth, a test suite generation tool, is based on this concept. We report on(More)
System testing of software with command language interfaces can be automated using grammar based test generation or through generating tests from an application domain speciication. When viewing test case generation as constructing a sequence of commands to achieve a testing goal, AI planning systems appear very promising. This paper reports on automated(More)