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A REGRESSION TESTING SYSTEM FOR GRID ADAPTIVE COMPUTATIONAL ENGINE

OF THE THESIS A Regression Testing System for Grid Adaptive Computational Engine by Dhaval Kapadia Thesis Director: Professor Manish Parashar GrACE (Grid Adaptive Computational Engine) is an adaptive computational and data-management engine for enabling distributed adaptive mesh-refinement computations on structured grids. Constant updates to this software and its critical functionality presents a need for an efficient and effective method of testing it. In this work, we have implemented regression testing of GrACE to ensure that changes made to it, such as adding new features or modifying existing features, do not adversely affect the current functionality of the software. We have studied and compared various regression testing systems and test case generation methodologies. A regression testing system has been developed using the DejaGnu test framework which uses Expect based scripting for the design of test cases. It is then analyzed for its effectiveness in testing GrACE. Various test cases have been identified for a representative subset of classes. A modification based approach is used to identify the part of software to be tested. Test case minimization and prioritization is implemented and evaluated for its effectiveness in testing.