Title: Combination and mutation strategies to support test data generation in the context of autonomous vehicles
Authors: Vânia De Oliveira Neves; Márcio Eduardo Delamaro; Paulo Cesar Masiero
Addresses: Depto de Sistemas de Computação – ICMC, Universidade de São Paulo – São Carlos, SP, Brasil ' Depto de Sistemas de Computação – ICMC, Universidade de São Paulo – São Carlos, SP, Brasil ' Depto de Sistemas de Computação – ICMC, Universidade de São Paulo – São Carlos, SP, Brasil
Abstract: The software used to control autonomous vehicles is a type of embedded system that needs to undergo strenuous testing before deployment. Field testing is the final stage of testing ensuring that autonomous vehicles show the intended behaviour. It usually does not take into consideration the code structure. In this context, a previously proposed testing model and a software tool to support structural testing in the context of autonomous vehicle field testing have been improved to support the generation of new input data from logs collected during field testing using strategies of combination and mutation. We present in this paper three combination strategies and five mutation strategies with the objective of being used in a search-based algorithm for structural data testing generation. A study to assess their coverage according to the criteria all-nodes and all-edges is also shown.
Keywords: structural software testing; autonomous vehicles; autonomous vehicle testing; test data generation; combination strategies; mutation strategies; search-based testing; point clouds; embedded systems.
International Journal of Embedded Systems, 2016 Vol.8 No.5/6, pp.464 - 482
Received: 12 Feb 2015
Accepted: 06 Sep 2015
Published online: 17 Nov 2016 *