Stochastic Contracts for Runtime Checking of Component-based Real-time Systems

TL;DR

This paper presents a statistical inference-based technique for dynamically verifying functional and real-time properties of component-based systems, enhancing reliability with minimal overhead.

Contribution

It introduces a novel contract framework that incorporates statistical inference to specify and verify real-time properties of off-the-shelf components.

Findings

Framework integrates into control applications smoothly

Achieves verification with less than 10% overhead

Effective in industrial case studies

Abstract

This paper introduces a new technique for dynamic verification of component-based real-time systems based on statistical inference. Verifying such systems requires checking two types of properties: functional and real-time. For functional properties, a standard approach for ensuring correctness is Design by Contract: annotating programs with executable pre- and postconditions. We extend contracts for specifying real-time properties. In the industry, components are often bought from vendors and meant to be used off-the-shelf which makes it very difficult to determine their execution times and express related properties. We present a solution to this problem by using statistical inference for estimating the properties. The contract framework allows application developers to express contracts like "the execution time of component $X$ lies within $\gamma$ standard deviations from the mean execution time". Experiments based on industrial case studies show that this framework can be smoothly integrated into existing control applications, thereby increasing their reliability while having an acceptable execution time overhead (less than 10%).