Automata Learning for Automated Test Generation of Real Time Localization Systems

TL;DR

This paper presents an automata learning-based method for automatic test case generation in real-time localization systems, a complex and safety-critical class of cyber-physical systems, demonstrated through a case study.

Contribution

It introduces a novel procedure combining automata learning with test case generation specifically for real-time localization systems in CPSs.

Findings

Successfully generated test cases for RTLSs

Automata models aid in system understanding and testing

Applicable to safety-critical CPSs

Abstract

Cyber Physical Systems (CPSs) are often black box systems for which no exact model exists. Automata learning allows to build abstract models of CPSs and is used in several scenarios, i.e. simulation, monitoring, and test case generation. Real time localization systems (RTLSs) are an example of particularly complex and often safety critical CPSs. We present a procedure for automatic test case generation with automata learning and apply this approach in a case study to a localization system.