We present methodology, which allows automatically test database schemes. Such methodology allows you to create new one or expand existing CASE tool. You can integrate database tests in generating physical database model process. In this way you can make scheme validation much easier, as a result it lowers the possibility of errors in early steps of modelling. Acording to our analysis, there are very few tools that covers such methodotlogy. So during our work we have designed and created a new tool – „DbTestAddin“, tool that tests database schemes. It works as Microsoft Office Visio 2003 Add-in. With this tool you can easily test any database scheme you want, compare it with a real database etc. In future, there are several updates and functional enhacements which can make this tool more attractive to use.

Test suites for database applications depend on adequate test data and real-world test faults for success. An automated tool is available that quantifies test data coverage for database queries written in SQL. An automated tool is also available that mimics real-world faults by mutating SQL, however tests have revealed that these simulated faults do not completely represent real-world faults. This paper demonstrates how half of the mutation operators used by the SQL mutation tool in real-world test suites generated significantly lower detection scores than those from research test suites. Three revised mutation operators are introduced that improve detection scores and contribute toward re-defining a sufficient set of mutation operators for SQL. Finally, a procedure is presented that reduces the test burden by automatically comparing SQL mutants with their original queries. / Master of Science

This dissertation presents a novel methodology based on test summaries, which characterize desired tests as constraints written in a mixed imperative and declarative notation, for automated systematic testing of relational applications, such as relational database engines. The methodology has at its basis two novel techniques for effective and efficient testing: (1) mixed-constraint solving, which provides systematic generation of inputs characterized by mixed-constraints using translations among different data domains; and (2) clustered test execution, which optimizes execution of test suites by leveraging similarities in execution traces of different tests using abstract-level undo operations, which allow common segments of partial traces to be executed only once and the execution results to be shared across those tests. A prototype embodiment of the methodology enables a novel approach for systematic testing of commonly used database engines, where test summaries describe (1) input SQL queries, (2) input database tables, and (3) expected output of query execution. An experimental evaluation using the prototype demonstrates its efficacy in systematic testing of relational applications, including Oracle 11g, and finding bugs in them. / text