L3R:基于图神经网络的日志语句级别推荐方法研究OA

Due to the lack of a rigorous specification to guide logging behaviors,choosing the correct level for log statements is a challenge.Prior studies on log level suggestion ignore the relationship between statements and fail to provide suggestions for logging statements at any specific positions.Based on this,L3R,a GNN-based log level suggest method,is proposed.The method took statement features as nodes,control flow and data flow edges as edges to construct a context graph,updated the logging statement feature based on the relational graph attention network and implemented the log level prediction.Evaluations were conducted on 7 open-source projects,which verified the effectiveness of the method.