Using Formal Methods for Autonomous Systems: Five Recipes for Formal Verification
This position paper provides practical recipes for formal verification to improve the safety and reliability of autonomous systems, which are increasingly deployed in everyday settings.
This paper presents five methods for formally verifying autonomous systems, addressing the need for robust development and verification in these safety-critical systems. It demonstrates how formal methods can be used for unambiguous requirement description, verification of specifications against requirements, synthesis of software components, and runtime behavior monitoring.
Formal Methods are mathematically-based techniques for software design and engineering, which enable the unambiguous description of and reasoning about a system's behaviour. Autonomous systems use software to make decisions without human control, are often embedded in a robotic system, are often safety-critical, and are increasingly being introduced into everyday settings. Autonomous systems need robust development and verification methods, but formal methods practitioners are often asked: Why use Formal Methods for Autonomous Systems? To answer this question, this position paper describes five recipes for formally verifying aspects of an autonomous system, collected from the literature. The recipes are examples of how Formal Methods can be an effective tool for the development and verification of autonomous systems. During design, they enable unambiguous description of requirements; in development, formal specifications can be verified against requirements; software components may be synthesised from verified specifications; and behaviour can be monitored at runtime and compared to its original specification. Modern Formal Methods often include highly automated tool support, which enables exhaustive checking of a system's state space. This paper argues that Formal Methods are a powerful tool for the repertoire of development techniques for safe autonomous systems, alongside other robust software engineering techniques.