Automata theory provides a rigorous framework for modeling, analyzing, and verifying systems in both network protocols and bioinformatics. By abstracting complex systems into states and transitions, automata allow for the systematic exploration of system behavior, making it easier to detect errors, optimize performance, and understand underlying biological processes. This cross-disciplinary application of automata theory highlights its versatility and power in tackling real-world challenges.
One of the drawbacks of using automata for specifications directly is the complexity you run into for real systems. It is also not trivial (or possible at all) to specify communication between two or more automata that have to cooperate.
Therefore, you might want to look into process algebras, which allow you to specify parallel communicating systems on a much higher level. Personally I use ACP and the mCRL2 Tool Set.
In this setting the mCRL2 tools generate a Labelled Transition System (LTS) from a high-level specification to explore its behaviour and use it as a basis for proofs. In essence an LTS is an automaton from automata theory.
One could say: "automata are the assembler level to the high(er)-level process algebras".
For real-world specification examples in a slightly older process algebra language (PSF) you could check "Algebraic Specification of Communication Protocols" (Mauw & Veltink).
Automata theory provides a formal framework that can be applied to model, verify, and analyze digital and biological systems, such as DNA sequences. The abstract nature of automata allows for the precise and systematic handling of complex processes, so it is an invaluable tool in these fields.
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