A system identification based Oracle for control-CPS software fault localization
Refereed conference paper presented and published in conference proceedings


摘要Control-CPS software fault localization (SFL, aka bug localization) is of critical importance as bugs may cause
major failures, even injuries/deaths. To locate the bugs in control-CPSs, SFL tools often demand many labeled (“correct”/“incorrect”) source code execution traces as inputs. To label the correctness of these traces, we must judge the corresponding control-CPS physical trajectories’ correctness. However, unlike discrete outputs, the boundaries between correct and incorrect physical trajectories are often vague. The mechanism (aka oracle) to judge the physical trajectories’ correctness thus becomes a major challenge. So far, the ad hoc practice of “human oracles”
is still widely used, whose qualities heavily depend on the human experts’ expertise and availability. This paper proposes an oracle based on the well adopted autoregressive system identification (AR-SI). With proven success for controlling black-box physical systems, AR-SI is adapted by us to identify the buggy controlCPS as a black-box. We use this identification result as an oracle to judge the control-CPS’s behaviors, and propose a methodology to prepare traces for control-CPS debugging. Comprehensive evaluations on classic control-CPSs with injected real-life and artificial bugs show that our proposed approach significantly outperforms the human oracle approach in SFL accuracy (recall) and latency, and in oracle false positive/negative rates. Our approach also helps discover a new real-life bug in a consumergrade control-CPS.
著者Zhijian He, Yao Chen, Enyan Huang, Qixin Wang, Yu Pei, Haidong Yuan
會議名稱41st IEE/ACM International Conference on Software Engineering
會議地點Montreal, Quebec, Canada
會議論文集題名ICSE '19 Proceedings of the 41st International Conference on Software Engineering
出版地IEEE Press Piscataway, NJ, USA
頁次116 - 127

上次更新時間 2021-04-05 於 00:48