Physical Sciences and Mathematics Commons^™

Identifying Bug Signatures Using Discriminative Graph Mining, Hong Cheng, David Lo, Yang Zhou, Xiaoyin Wang, Xifeng Yan

David LO

Bug localization has attracted a lot of attention recently. Most existing methods focus on pinpointing a single statement or function call which is very likely to contain bugs. Although such methods could be very accurate, it is usually very hard for developers to understand the context of the bug, given each bug location in isolation. In this study, we propose to model software executions with graphs at two levels of granularity: methods and basic blocks. An individual node represents a method or basic block and an edge represents a method call, method return or transition (at the method or basic …