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)
In general, the test data generation problem is equivalent to the Halting Problem; therefore, it is undecidable. This does not have to be the case for speciic problem domains. We propose a solution to the test data generation problem for command-based systems, and we call our method Domain Based Testing (DBT). DBT uses Domain Analysis and a Domain Model to(More)
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