  This paper presents an automated tool called Morphy for datamorphic testing.
It classifies software test artefacts into test entities and test morphisms,
which are mappings on testing entities. In addition to datamorphisms,
metamorphisms and seed test case makers, Morphy also employs a set of other
test morphisms including test case metrics and filters, test set metrics and
filters, test result analysers and test executers to realise test automation.
In particular, basic testing activities can be automated by invoking test
morphisms. Test strategies can be realised as complex combinations of test
morphisms. Test processes can be automated by recording, editing and playing
test scripts that invoke test morphisms and strategies. Three types of test
strategies have been implemented in Morphy: datamorphism combination
strategies, cluster border exploration strategies and strategies for test set
optimisation via genetic algorithms. This paper focuses on the datamorphism
combination strategies by giving their definitions and implementation
algorithms. The paper also illustrates their uses for testing both traditional
software and AI applications with three case studies.
