布谷鸟搜索
测试套件
计算机科学
正确性
基于搜索的软件工程
软件
测试用例
背景(考古学)
算法
构造(python库)
软件建设
软件开发
机器学习
程序设计语言
粒子群优化
生物
古生物学
回归分析
作者
Bestoun S. Ahmed,Taib Sh. Abdulsamad,Moayad Yousif Potrus
标识
DOI:10.1016/j.infsof.2015.05.005
摘要
Software has become an innovative solution nowadays for many applications and methods in science and engineering. Ensuring the quality and correctness of software is challenging because each program has different configurations and input domains. To ensure the quality of software, all possible configurations and input combinations need to be evaluated against their expected outputs. However, this exhaustive test is impractical because of time and resource constraints due to the large domain of input and configurations. Thus, different sampling techniques have been used to sample these input domains and configurations. Combinatorial testing can be used to effectively detect faults in software-under-test. This technique uses combinatorial optimization concepts to systematically minimize the number of test cases by considering the combinations of inputs. This paper proposes a new strategy to generate combinatorial test suite by using Cuckoo Search concepts. Cuckoo Search is used in the design and implementation of a strategy to construct optimized combinatorial sets. The strategy consists of different algorithms for construction. These algorithms are combined to serve the Cuckoo Search. The efficiency and performance of the new technique were proven through different experiment sets. The effectiveness of the strategy is assessed by applying the generated test suites on a real-world case study for the purpose of functional testing. Results show that the generated test suites can detect faults effectively. In addition, the strategy also opens a new direction for the application of Cuckoo Search in the context of software engineering.
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