Automata Theory: inside a RegExp machine

Description :

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Course overview State machines — the fundamental concept used today in many practical applications, starting from UI programming like React, automated reply systems, lexical analysis in parsers and formal language theory — i.e. the RegExp machines, — and up to real life use cases, such as simple traffic lights, vending machines, and others. The state machines are backed by the larger theoretical field of computer science known as Theory of Computation, and also by its direct theoretical model — the Automata Theory. In this class we study the Automata Theory on the practical example of implementing a Regular Expressions machine. Why to take this class? It’s not a secret, that big tech companies, such as Google, Facebook, etc. organize their recruiting process around generalist engineers, which understand basic fundamental systems, data structures, and algorithms. In fact, it’s a known issue in tech-recruiting: there are a lot of “programmers”, but not so many “engineers”. And what does define an “engineer” in this case? — an ability so solve complex problems, with understanding (and experience) in those generic concepts. And there is a simple trick how you can gain a great experience with transferable knowledge to other systems. — You take some complex theoretical field, which might not (yet) be related to your main job, and implement it in a language you’re familiar with. And while you build it, you learn all the different data structures and algorithms, which accommodate this system. It should specifically be something generic (for example, State machines), so you can further transfer this knowledge to your “day-to-day” job. In this class we take this approach. To study Automata “Theory” we make it more practical: we take one of its widely-used applications, the lexical analysis, and pattern matching, and build a RegExp machine. Not only we’ll completely understand how the Regular Expressions work under the hood (and what will make their usage more professional), but also will be able to apply this knowledge about formal grammars, languages, finite automata — NFAs, DFAs, etc — in other fields of our work.