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Global Optimization for Combination Test Suite by Cluster Searching Algorithm 认领 引用 被引量：1
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作者 Hao Chen Xiaoying Pan Jiaze Sun 《自动化学报》 EI CAS CSCD 北大核心 2017年第9期1625-1635,共11页
The test suite generation is a key task for combinatorial testing of software. In order to generate high-quality testing data, a cluster searching driven global optimization mechanism is proposed. In this approach, a ... The test suite generation is a key task for combinatorial testing of software. In order to generate high-quality testing data, a cluster searching driven global optimization mechanism is proposed. In this approach, a binary encoding mechanism is used to transform the combination test suite generating problem into a gene sequence optimization problem. Meanwhile, a novel global optimization algorithm, cluster searching algorithm （CSA）, is developed to solve it. In this paper, the validity and rationality of problem transformation mechanism is verified, and the details of CSA are shown. The simulations illustrate the proposed mechanism is feasible. Moreover, it is a simpler and more efficient test suite generation approach for small-size combinatorial testing problems. 展开更多
关键词 Cluster searching algorithm （CSA）, combination test, global optimization, test suite optimization
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