Spectrum-Based Fault Localization (SBFL) is a popular technique to assist developers in pinpointing faulty elements within their code based on test outcomes and code coverage. In this paper, we examine the impact of context switching, i.e., when developers must frequently shift their attention between different code parts (such as methods and classes) while searching for the faulty statement within the SBFL ranked list. The basis of our study is the observation that it requires less effort to investigate statements that are next to each other rather than those in different methods and classes. In particular, we analyse the number of visited methods and classes, as well as the frequency of switches between them during the fault localization process. We found that, in programs from the Defects4J benchmark, developers need to explore 40 methods and 12 classes on average, before finding the faulty statement, leading to 53 method- and 40 class switches, respectively.

We introduce a novel context-aware metric that better approximates the total cost of finding a bug than traditional metrics that solely count the number of statements. Our metric considers both the statement number and the added cost of context switches. Furthermore, we propose a new algorithm to optimize the traversal of the elements in the ranked list based on the new context-aware metric. The algorithm not only lowers the number of statements that need to be investigated by 12% but also significantly reduces the number of class and method switches by 52%.