El Farissi, I., Azizi, M., Lanet, J.L. and Moussaoui, M. (2013) Neural Network vs. Bayesian Network to Detect Java Card Mutants. Agriculture and Agricultural Science Procedia, 4, 132-137.
http://dx.doi.org/10.1016/j.aasri.2013.10.021

has been cited by the following article:

• TITLE: Automatic Test Data Generation for Java Card Applications Using Genetic Algorithm

  AUTHORS: Saher Manaseer, Warif Manasir, Mohammad Alshraideh, Nabil Abu Hashish, Omar Adwan

  KEYWORDS: Software Testing, Genetic Algorithm, Java Smart Card

  JOURNAL NAME: Journal of Software Engineering and Applications, Vol.8 No.12, December 24, 2015

  ABSTRACT: The main objective of software testing is to have the highest likelihood of finding the most faults with a minimum amount of time and effort. Genetic Algorithm (GA) has been successfully used by researchers in software testing to automatically generate test data. In this paper, a GA is applied using branch coverage criterion to generate the least possible set of test data to test JSC applications. Results show that applying GA achieves better performance in terms of average number of test datagenerations, execution time, and percentage of branch coverage.