Distributed Analysis for Diagnosability in Concurrent Systems

TL;DR

This paper presents a distributed approach to analyze diagnosability in complex concurrent systems, enabling fault detection by analyzing components separately and combining results, with a prototype tool demonstrating effectiveness.

Contribution

It introduces a novel distributed method for diagnosability analysis of concurrent systems with multiple faults, including a practical implementation.

Findings

Distributed diagnosability analysis is feasible for complex systems.

The approach effectively detects faults in concurrent components.

Prototype tool shows promising results in real-world examples.

Abstract

Complex systems often exhibit unexpected faults that are difficult to handle. Such systems are desirable to be diagnosable, i.e. faults can be automatically detected as they occur (or shortly afterwards), enabling the system to handle the fault or recover. A system is diagnosable if it is possible to detect every fault, in a finite time after they occurred, by only observing the available information from the system. Complex systems are usually built from simpler components running concurrently. We study how to infer the diagnosability property of a complex system (distributed and with multiple faults) from a parallelized analysis of the diagnosability of each of its components synchronizing with fault free versions of the others. In this paper we make the following contributions: (1) we address the diagnosability problem of concurrent systems with arbitrary faults occurring freely in each component. (2) We distribute the diagnosability analysis and illustrate our approach with examples. Moreover, (3) we present a prototype tool that implements our techniques showing promising results.