Bug Reproduction Based on EFSM Model
ChengQian Ren, Ying Shang · 2021
Bug reproduction is an important task for uncovering the causes of the bug and providing appropriate fixes. However, this task is usually labor-intensive and time-taking. Several solutions have been proposed to automate this task. The proposed solutions typically either use program runtime data, or bug stack traces to generate a test case that triggers the represented bug. In this paper, we propose a novel bug reproduction approach that combines the bug information and extended finite state machine model to generate effective test cases needed to reproduce a bug. The experimental results of 15 bugs in four common systems show that the proposed method can quickly and accurately reproduce bugs.