Analyzing Corrective Maintenance using Change Coupled Clusters at Fix-inducing Changes

Abstract

Due to changing nature of change coupled relation, corrective maintenance of any software system is costly. Existing works on change coupled relation analyzed different areas like change prediction or impact. But, none of those tried to utilize historical information to analyze system maintenance. In this paper, a methodology is proposed by using change coupled relations at fix introducing changes to analyze the corrective maintenance history of the system. This analysis helps to understand which part of the system are prone to erroneous changes.