Abstract : Search-based testing generates test cases by encoding an adequacy criterion as the fitness function that drives a search-based optimization algorithm. Genetic algorithms have been successfully applied in search-based testing: while most of them use adequacy criteria based on the structure of the program, some try to maximize the mutation score of the test suite.This work presents a genetic algorithm for generating a test suite for mutation testing. The algorithm adopts several features from existing bacteriological algorithms, using single test cases as individuals and keeping generated individuals in a memory. The algorithm can optionally use automated seeding when producing the first population, by taking into account interesting constants in the source code.We have implemented this algorithm in a framework and we have applied it to a WS-BPEL composition, measuring to which extent the genetic algorithm improves the initial random test suite. We compare our genetic algorithm, with and without automated seeding, to random testing.
https://hal.inria.fr/hal-01405261 Contributor : Hal IfipConnect in order to contact the contributor Submitted on : Tuesday, November 29, 2016 - 4:31:33 PM Last modification on : Tuesday, November 29, 2016 - 4:38:34 PM Long-term archiving on: : Monday, March 27, 2017 - 9:05:08 AM
Antonia Estero-Botaro, Antonio García-Domínguez, Juan José Domínguez-Jiménez, Francisco Palomo-Lozano, Inmaculada Medina-Bulo. A Framework for Genetic Test-Case Generation for WS-BPEL Compositions. 26th IFIP International Conference on Testing Software and Systems (ICTSS), Sep 2014, Madrid, Spain. pp.1-16, ⟨10.1007/978-3-662-44857-1_1⟩. ⟨hal-01405261⟩