An Empirical Study on Leveraging Logs for Debugging Production Failures

In modern software development, maintenance is one of the most expensive processes. When end-users encounter software defects, they report the bug to developers by specifying the expected behavior and error messages (e.g., log message). Then, they wait for a bug fix from the developers. However, on the developers' side, it can be very challenging and expensive to debug the problem. To fix the bugs, developers often have to play the role of detectives: seeking clues in the user-reported logs files or stack trace in a snapshot of specific system execution. This debugging process may take several hours or even days. In this paper, we first look at the usefulness of the user-reported logs. Then, we propose an automated approach to assist the debugging process by reconstructing the execution path. Through the analysis, our investigation shows that 31% of the time, developer further requests logs from the reporter. Moreover, our preliminary results show that the reconducted path illustrates the user's execution. We believe that our approach proposes a novel solution in debugging production failures.