基于选择性冗余的测试数据自动生成算法

基于选择性冗余思想，提出了一种测试数据自动生成算法.算法首先利用分支函数线性逼近和极小化方法，找出程序中所有可行路径，同时对部分可行路径自动生成适合的初始测试数据集；当利用分支函数线性逼近和极小化方法无法得到正确的测试数据时，基于使得测试数据集最小的原理和选择性冗余思想，针对未被初始测试数据集覆盖的谓词和子路径进行测试数据的增补.由于新算法结合谓词切片和DUC表达式，可以从源端判断子路径是否可行，因此能有效地降低不可行路径对算法性能的影响.算法分析和实验结果表明，该算法有效地减少了测试数据数量，提高了测试性能.

An Automated Test Data Generation Algorithm Based on Selective Redundancy

Automated test data generation has become a hot point in the research of software tests,and lots of useful models and methods have been proposed by researchers,but the performances of these existing schemes are not very satisfactory.So,it is very important to study how to design new automated methods with high performances for test data generation.Based on selective redundancy,a new automated test data generation algorithm is proposed,which firstly adopts methods such as linear approximation and minimizatio...