Morphy: A Datamorphic Software Test Automation Tool
This tool addresses the problem of automating software testing processes for developers and testers, but it appears incremental as it builds on existing datamorphic testing concepts.
The paper introduces Morphy, an automated tool for datamorphic testing that classifies test artefacts into entities and morphisms to automate basic activities, strategies, and processes, with a focus on datamorphism combination strategies demonstrated through three case studies on traditional software and AI applications.
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.