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Aspect-oriented programming (AOP) is gaining popularity with the wider adoption of languages such as AspectJ. During AspectJ software evolution, when regression tests fail, it may be tedious for programmers to find out the failure-inducing changes by manually inspecting all code editing. To eliminate the expensive effort spent on debugging, we developed AutoFlow, an automatic debugging tool for AspectJ software. AutoFlow integrates the potential of delta debugging algorithm with the benefit of change impact analysis to narrow down the search for faulty changes. It first uses change impact analysis to identify a subset of responsible changes for a failed test, then ranks these changes according to our proposed heuristic (indicating the likelihood that they may have contributed to the failure), and finally employs an improved delta debugging algorithm to determine a minimal set of faulty changes. The main feature of AutoFlow is that it can automatically reduce a large portion of irrelevant changes in an early phase, and then locate faulty changes effectively.