Knowledge fusion based on D-S theory and its application on Expert System for software fault diagnosis

Expert systems are widely used for software fault diagnosis. Knowledge in these Expert Systems could be learned from different ways, such as human expert, machine learning and etc.. The scale of the knowledge is increasing quickly, due to the development of testing tools and techniques. However, it is a big challenge to integrate the knowledge from different sources. In this paper, a novel knowledge fusion method based on D-S theory is provided to meet the challenge and its application on practical software fault diagnosis shows satisfied results.