A Framework for Optimization of Software Test Cases Generation using Cuckoo Search Algorithm

被引：0
作者：
Sharma, Sanjiv [1 ]
Rizvi, S. A. M. [2 ]
Sharma, Vineet [1 ]
机构：
[1] KIET Grp Inst, Dept Comp Sci & Engn, Ghaziabad, UP, India
[2] Jamia Millia Islamia, Dept Comp Sci, New Delhi, India
来源：
2019 9TH INTERNATIONAL CONFERENCE ON CLOUD COMPUTING, DATA SCIENCE & ENGINEERING (CONFLUENCE 2019) | 2019年
关键词：
Software Testing; Cuckoo Search Algorithm; Le'vy Flight;
D O I：
10.1109/confluence.2019.8776898
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Software testing is the most important phase of the software development lifecycle in the software industry. It is done to make sure that developed software is defect free; behavior of the software is same as expected and includes the generation of test data that satisfies some adequacy criteria like statement coverage, branch coverage, path coverage etc. This task is costly and time-consuming so there is an urge for automation of this process. In recent years various meta-heuristic based nature-inspired algorithms are applied in various fields of software engineering. This article proposes a framework for the generation of an optimal set of test cases using a meta-heuristic based optimization algorithm called Cuckoo Search Algorithm as well as an overall algorithm for the same.
引用
收藏
页码：282 / 286
页数：5
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