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Verification and Validation in the Context of DSM

Verification and Validation in the Context of DSM. Janne Merilinna, Olli-Pekka Puolitaival, John Menke, Tihamer Levendovszky, Jonathan Sprinkle, Mika Karaila, Edgars Rencis, Hiroshi Kazato, Takashi Kopayashy. Table of Context. Metamodel Testing Code Generator Testing Model Testing

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Verification and Validation in the Context of DSM

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  1. Verification and Validation in the Context of DSM Janne Merilinna, Olli-Pekka Puolitaival, John Menke, Tihamer Levendovszky, Jonathan Sprinkle, Mika Karaila, Edgars Rencis, Hiroshi Kazato, Takashi Kopayashy

  2. Table of Context • Metamodel Testing • Code Generator Testing • Model Testing • Conclusion

  3. Metamodel Testing • Causes of Errors • Metamodel does not cover the problem domain • Metamodel does not fit to the framework • Error categories • Missing rules • Missing associations • Missing constrains • Missing cardinality • Missing entities • How to test the metamodels • Verification • We need to have a huge number of test cases, i.e. application models • But we cannot verify the metamodel as such

  4. Code Generator Testing • Causes of errors • Templates are wrong • Logic of the code generators is wrong • Testing • Metamodel limits the input • Application models are the input, i.e. the test cases for code generator • We don’t want to test only the code generator • From research point of view this might be interesting • Practice?

  5. Model Testing • Causes of errors • Incorrect metamodel • Formal methods • Transforming application models to something else where we can apply formal methods • Petri Net etc. • Deadlock • Structure semantics • Etc. • Does these kind of tests really say anything in practice • You still have to generate code and you still have your framework on which you generate code • BUT can you detect something earlier? • Model-Based Testing?

  6. Conclusion • Sun was shining • The beer was good • Loud discussions • Which was good • However • To be continued in the next SPLASH (OOPSLA) DSM’10

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