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Full Description
The theory of computation is used to address challenges arising in many computer science areas such as artificial intelligence, language processors, compiler writing, information and coding systems, programming language design, computer architecture and more. To grasp topics concerning this theory readers need to familiarize themselves with its computational and language models, based on concepts of discrete mathematics including sets, relations, functions, graphs and logic.
This handbook introduces with rigor the important concepts of this kind and uses them to cover the most important mathematical models for languages and computation, such as various classical as well as modern automata and grammars. It explains their use in such crucially significant topics of computation theory as computability, decidability, and computational complexity. The authors pay special attention to the implementation of all these mathematical concepts and models and explains clearly how to encode them in computational practice. All computer programs are written in C#.
Contents
Part I: Basic mathematical concepts
Chapter 1: Sets, sequences, and languages
Chapter 2: Relations and functions
Chapter 3: Graphs
Part II: Classical models for languages and computation
Chapter 4: Relations and language models
Chapter 5: Finite automata
Chapter 6: Context-free grammars
Chapter 7: Pushdown automata
Chapter 8: Turing machines
Chapter 9: Computability
Chapter 10: Decidability
Part III: Alternative models for languages and computation
Chapter 11: Context-dependent grammars
Chapter 12: Regulated models
Chapter 13: Parallel grammatical models
Chapter 14: Jumping models
Chapter 15: Deep pushdown automata
Part IV: Applications
Chapter 16: Applications in general
Chapter 17: Applications in syntax analysis: programming languages
Chapter 18: Applications in syntax analysis: natural languages
Chapter 19: Applications in biology
Part V: Conclusion
Chapter 20: Concluding remarks
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