Comprehending performance from real-world execution traces: A device-driver case

Real-world execution traces record performance problems that are likely perceived at deployment sites. However, those problems can be rooted subtly and deeply into system lay-ers or other components far from the place where delays are initially observed. To tackle challenges of identifying deeply rooted problems, we propose a new trace-based ap-proach consisting of two steps: impact analysis and causality analysis. The impact analysis measures performance impacts on a component basis, and the causality analysis discovers patterns of runtime behaviors that are likely to cause the measured impacts. The discovered patterns can help perfor-mance analysts quickly identify root causes of perceived per-formance problems. We instantiate our approach to study the performance of device drivers on over 19,500 real-world ex-ecution traces. The impact analysis shows that device drivers constitute a non-trivial part ( ≈ 38%) in the overall system performance, and a big part ( ≈ 26%) is due to interactions between drivers. The causality analysis effectively discov-ers highly suspicious and high-impact behavioral patterns in device drivers, examined and confirmed by our automated evaluation, developers, and performance analysts