Supervision of real-time software systems using optimistic path prediction and rollbacks

Abstract

Real time supervision is a technique for automatically detecting and reporting failures in the external behaviour of real time software systems. Failure detection is achieved by monitoring the target system's external inputs and outputs, in a 'black box' manner and comparing its behaviour with the formally specified behaviour of the system. The paper presents the Optimistic Path Prediction and Rollbacks (OPPR) approach to real time supervision. In this technique, the supervisor predicts a single likely behaviour of the target system and, if the observed behaviour does not match the prediction, rolls back and creates a new prediction of the legal behaviour. A failure is detected when the supervisor has explored all valid behaviours without matching the observed behaviour. The paper opens by introducing the field of real time supervision and examining existing techniques. The core of the paper presents the basic algorithm of the OPPR method, with an example to illustrate its operation. The paper closes by describing an evaluation system, summarizing the experimental results and examining the performance of the OPPR scheme.