Novel Evolutionary Generation Approach to Test Data for Multiple Paths Coverage
电子学报2010年38卷第6期 页码:1299-1304
作者机构:
1. 1. 中国矿业大学信息与电气工程学院,江苏,徐州,221116
2. 牡丹江师范学院计算机科学与技术系,黑龙江,牡丹江,157012
作者简介:
基金信息:
DOI:
中图分类号:TP301
纸质出版:2010
稿件说明:
移动端阅览
FONT face, Verdana, 巩敦卫, 等. 一种新的多路径覆盖测试数据进化生成方法[J]. 电子学报, 2010,38(6):1299-1304.
FONT face, Verdana, GONG Dun-wei, et al. Novel Evolutionary Generation Approach to Test Data for Multiple Paths Coverage[J]. Acta Electronica Sinica, 2010, 38(6): 1299-1304.
FONT face, Verdana, 巩敦卫, 等. 一种新的多路径覆盖测试数据进化生成方法[J]. 电子学报, 2010,38(6):1299-1304.DOI:
FONT face, Verdana, GONG Dun-wei, et al. Novel Evolutionary Generation Approach to Test Data for Multiple Paths Coverage[J]. Acta Electronica Sinica, 2010, 38(6): 1299-1304.DOI:
<FONT face=Verdana>A novel approach to generate test data for multiple paths coverage is presented. First
the program under test is expressed as a binary tree
and the target paths are encoded into a binary string using Huffman coding; then
genetic algorithm is employed to generate multiple test data
an individual’s fitness is the degree of the traversed path matching the target paths. The proposed approach is applied to 4 benchmark programs
and compared it with previous approaches. The results show that the proposed approach needs small amount of calculation and has high efficiency in generating test data.