Automated Test Oracle Based on Neural Networks

摘要：

In this paper an attempt has been made to explore the possibility of the usage of artificial neural networks as automated test oracle. Automated test oracle includes capabilities to generate expected output and compare it with actual output automatically. It is important for automated software testing. But there are very few techniques to implement it. In this paper, an insensitive oracle is proposed. It generates approximate output that is close to expected output. The actual output is then compared with the approximate output in an interval. The relation between inputs and outputs of an application under testing is described as a function. When it is a continue Junction, neural networks are used to estimate the output after training. By the method, automated oracle can be implemented and precision be adjusted by parameters. It can save a lot of time and labor in software testing.

关键词： Test oracle neural networks software testing.

作者: Mao Ye Boqin Feng Li Zhu Yao Lin

作者单位: School of Electronics and Information Engineering, Xian Jiaotong University, Xian 710049, China School of Software Engineering, Xian Jiaotong University, Xian 710049, China

会议类型: 国际会议

会议名称: Firth IEEE International Conference on Cognitive Informatics(第五届认知信息国际会议)

会议地点: 北京

会议语种:英文

页码: 517-522

在线出版日期: 2006-07-17（万方平台首次上网日期，不代表论文的发表时间）