Application of Negative Selection Algorithm (NSA) for test data generation of path testing

作     者：Mohi-Aldeen, Shayma Mustafa Mohamad, Radziah Deris, Safaai 

作者机构：Univ Teknol Malaysia Fac Comp Utm Skudai 81310 Johor Malaysia Univ Malaysia Kelantan Fac Teknol Kreatif Dan Warisan Kelantan 16100 Malaysia Univ Mosul Coll Comp Sci & Math Mosul 41002 Iraq 

出 版 物：《APPLIED SOFT COMPUTING》 (应用软计算)

年 卷 期：2016年第49卷

页      面：1118-1128页

核心收录：

学科分类：08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：Ministry of Higher Education Malaysia Ministry of Higher Education & Scientific Research of Iraq University of Mosul 

主　　题：Software testing Path testing Automatic test data generation Negative Selection Algorithm 

摘      要：Path testing is one of the areas covered in structural testing. In this process, it is a key challenge to search for a set of test data in the whole search space to satisfy path coverage. Thus, finding an efficient method for generating test data automatically is a key issue in software testing. This paper proposed a method based on Negative Selection Algorithm (NSA) for generating test data to satisfy the path coverage criterion. The results show that NSA could reduce the number of test data generated and improve the coverage percentage, as well as enhance the efficiency of the test data generation process. To evaluate the performance of the method, results from the proposed method were compared with random testing and a previous work that used Genetic Algorithm and Ant Colony Optimization. The results demonstrate that NSA outperforms other methods in reducing the number of test data that cover all program paths even the difficult ones. (C) 2016 Elsevier B.V. All rights reserved.