Search-based Testing using EFSMs

被引：0
|
作者：
Turlea, Ana [1 ,2 ]
机构：
[1] Univ Bucharest, Fac Math & Comp Sci, Bucharest, Romania
[2] Univ Bucharest, ICUB, Bucharest, Romania
来源：
2019 IEEE 30TH INTERNATIONAL SYMPOSIUM ON SOFTWARE RELIABILITY ENGINEERING WORKSHOPS (ISSREW 2019) | 2019年
关键词：
genetic algorithms; search based testing; test case generation; model based testing; extended finite state machines; multi objective genetic algorithm; nsga-iii;
D O I：
10.1109/ISSREW.2019.00052
中图分类号：
TP31 [计算机软件];
学科分类号：
081202 ; 0835 ;
摘要：
Extended finite state machines are widely used in model based testing. Since testing is such a critical step from the software development process, it is important to have many different test suites, generated on different criteria. This paper presents a test suite generation algorithm for EFSMs. The algorithm produces a set of feasible transition paths that cover all transitions using a modified NSGA-II and a NSGA-III Algorithm (based on different feasibility optimization) and a Hybrid Genetic Algorithm to generate input values that trigger all the paths.
引用
收藏
页码：100 / 103
页数：4
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