Towards an automation of the mutation analysis dedicated to model transformation. (25th April 2014)

• Record Type: Journal Article
• Authors: Aranega, Vincent; Mottu, Jean‐Marie; Etien, Anne; Degueule, Thomas; Baudry, Benoit; Dekeyser, Jean‐Luc
• Other Names: Jia Yue guestEditor.; Merayo Mercedes guestEditor.; Harman Mark guestEditor.
• Is Part Of: Software testing, verification & reliability. Volume 25:Number 5/7(2015)
• Page Start: 653
• Page End: 683
• Publication Date: 2014-04-25
• Subjects: MDE -- model transformation -- mutation analysis -- traceability -- mutation operator; Computer software -- Testing -- Periodicals; Computer software -- Verification -- Periodicals; Computer software -- Reliability -- Periodicals; 005.14
• DOI: 10.1002/stvr.1532
• Languages: English
• ISSNs: 0960-0833

Abstract

Summary: A benefit of model‐driven engineering relies on the automatic generation of artefacts from high‐level models through intermediary levels using model transformations. In such a process, the input must be well designed, and the model transformations should be trustworthy. Because of the specificities of models and transformations, classical software test techniques have to be adapted. Among these techniques, mutation analysis has been ported, and a set of mutation operators has been defined. However, it currently requires considerable manual work and suffers from the test data set improvement activity. This activity is a difficult and time‐consuming job and reduces the benefits of the mutation analysis. This paper addresses the test data set improvement activity. Model transformation traceability in conjunction with a model of mutation operators and a dedicated algorithm allow to automatically or semi‐automatically produce improved test models. The approach is validated and illustrated in two case studies written in Kermeta.Copyright © 2014 John Wiley & Sons, Ltd. Abstract : Mutation analysis for model transformations is perceived as cumbersome because of the test set improvement manual step that requires a strong expertise and analysis from the tester. This paper presents a solution to go towards a full automation of the mutation analysis for model transformations. This solution uses model transformation traceability and mutation operator modelization embedded into an assistant that helps the tester to easily create new test models to improve the test set. Copyright©2014 John Wiley & Sons, Ltd.