A Template–Based Approach to Describing Metamorphic Relations

Metamorphic testing enables the generation of test cases in the absence of an oracle by exploiting relations among different executions of the program under test, called metamorphic relations. In a recent survey, we observed a great variability in the way metamorphic relations are described, typically in an informal manner using natural language. We noticed that the lack of a standard mechanism to describe metamorphic relations often makes them hard to read and understand, which hinders the widespread adoption of the technique. In this paper, we propose a template–based approach for the description of metamorphic relations. The proposed template aims to ease communication among practitioners as well as to contribute to research dissemination. Also, it provides a helpful guide for those approaching metamorphic testing for the first time. For the validation of the approach, we used the proposed template to describe 17 previously published metamorphic relations from different domains and groups of authors, without finding expressiveness problems. We hope that this work eases the diffusion and adoption of metamorphic testing, contributing to the progress of this thriving testing technique.Comisión Interministerial de Ciencia y Tecnología TIN2015-70560-RJunta de Andalucía P12-TIC-186

Metamorphic testing: a review of challenges and opportunities

Metamorphic testing is an approach to both test case generation and test result verification. A central element is a set of metamorphic relations, which are necessary properties of the target function or algorithm in relation to multiple inputs and their expected outputs. Since its first publication, we have witnessed a rapidly increasing body of work examining metamorphic testing from various perspectives, including metamorphic relation identification, test case generation, integration with other software engineering techniques, and the validation and evaluation of software systems. In this paper, we review the current research of metamorphic testing and discuss the challenges yet to be addressed. We also present visions for further improvement of metamorphic testing and highlight opportunities for new research