An Experimental Protocol for Analyzing the Accuracy of Software Error Impact Analysis

In software engineering, error impact analysis consists in predicting the software elements (e.g. Modules, classes, methods) potentially impacted by a change. Impact analysis is required to optimize the testing effort. In this paper we present a new protocol to analyze the accuracy of impact analysis. This protocol uses mutation testing to simulate changes that introduce errors. To this end, we introduce a variant of call graphs we name the "use graph" of a software which may be computed efficiently. We apply this protocol to two open-source projects and correctly predict the impact of 30% to 49% of changes.