Theory of Computation Tutorials

Introduction to the Theory of Computation Lecture Notes

These are lecture notes from the University of Toronto, giving a very brief introduction to some of the basic ideas in the theory of computation. We start with some basic topics: induction and recursion; the correctness of programs, that must be understood if more advanced computational theories are to be enlightened. Then we go on to develop the topics of regular languages and finite automata, giving the basic models and techniques used in analysing and recognising regular languages. The coverage is designed to provide students with a reasonably solid grounding in the basic ideas of the theory of computation and to render a clear and thorough exposition of the fundamental concepts underlying more advanced topics.

Author(s): University of Toronto

75 Pages

Introduction to the Theory of Computing

Introduction to the Theory of Computing is a course that undertakes an intensive study of the underpinnings of the theory of computation. Beginning with mathematical foundations, the course moves into regular operations and expressions, and then into proofs on languages being nonregular and other further treatments on regular languages. Other important topics include parse trees, ambiguity, Chomsky normal form, pushdown automata, and Turing machines. Further, the PDF discusses various types of Turing machines, the stack machine model, and undecidable languages, making it a great starting point in the topic of computability.

Author(s): University of Waterloo

227 Pages

Models of Computation by John E. Savage

This book, written for graduates, covers general subjects on computational models, logic circuits, and memory machines, with advanced subjects being parallel computation, circuit complexity, and space-time trade-offs; therefore, it's a very thorough course on computational models and their complexities.

Author(s): John E. Savage, Brown University

698 Pages

Introduction to Computational Theory Lecture Notes

These broad-ranging notes introduce some of the fundamental concepts in the theory of computation. The set starts with a brief introduction to formal languages and their classification, including regular languages and sets. In these notes, finite automata are introduced, discussing their structure and role in recognizing regular languages. This is followed by Context-Free Grammars and Pushdown Automata, focusing on the role in defining and recognizing context-free languages. This will cover Turing Machines, the original model of computation; a review of the Chomsky Hierarchy from a perspective on the various levels of languages about their power of generation. The conclusion deals with an overview of Complexity Theory, mainly dealing with the P and NP problems. It gives insight into the computational complexity in general and into the famous P vs NP questions.

Author(s): BYU Computer Science Department

NA Pages

Introduction to Theory of Computation Lecture Notes

These lecture notes give an introduction to the more fundamental parts of the theory of computation and begin by presenting finite automata: starting with deterministic and nondeterministic finite automata, their equivalence, and practical implications of these concepts. The lecture notes include sections on regular expressions and their relationship to finite automata, non-regular languages, and the Pumping Lemma to prove non-regularity. Myhill-Nerode Theorem: For understanding recognition of languages. The notes go further to present context-free languages, including their ambiguity and properties of closure. The pumping lemma for context-free languages is also discussed, while decidable and recognizable languages are informed by a deep underpinning in computational theory.

Author(s): Mahesh Viswanathan

NA Pages

Advanced Theory in Computation

This is an advanced set of notes on the analysis of algorithms and their complexity. Of interest in these notes are the topics on string matching algorithms, such as Knuth-Morris-Pratt and Boyer-Moore. Suffix trees and dictionary techniques are also part of the discussion here. Among the methods to be shown in a way of analyzing algorithm efficiency are amortized analysis and randomized algorithms. It also treats the pairing technique, Ziv-Lempel coding; further topics on statistical adversaries, portfolio selection, and reservation-price policies that are objects of other techniques discussed herein.

Author(s): Seoul National University

NA Pages