Toward a defect prediction model of exception handling method call structures

Abstract

The ability to predict where faults are likely to arise in the source code can help guide test plans, reduce effort and cost, narrow the test space, and improve software quality. Our preliminary results show that exception handling code can be more risky than normal code. Therefore, in order to support more efficient testing of exception handling code, this extended abstract proposes a framework to predict faults from annotated exception handling method call structures. This framework will generate annotated exception call graphs of the whole system and calculate property-based software engineering measurement values. The framework will then predict the high risk area of the system by applying statistical modeling techniques to perform fault prediction.