Introduction to Theoretical Computer Science or Theory of Computation
Introduction to Theoretical Computer Science or Theory of Computation
Introduction to Theoretical Computer Science or Theory of Computation
This note covers the following
topics: introduction to theoretical computer science, language, regular
language, finite automata, language accepted by dfa, nondeterministic finite
automata, equivalence of nfa, regular language and fa, application of fa,
nonregular languages, context free languages, turing machines, computability
and complexity.
Author(s): Pavan
Kumar Anumula, Andrea Di Fabio and Jia Zhu
Frank Stephan's
detailed lecture notes on the theory of computation cover quite a wide spectrum
of issues. The document starts with the basics of sets and regular expressions,
then goes ahead to grammars and the Chomsky hierarchy, helping one in
understanding the structure of languages. Then it discusses finite automaton and
nondeterministic finite automata, giving all details about the processing of
strings by these models. The notes also treat the composition of languages,
normal forms, and algorithms used in computation. Membership testing, whether
deterministic or nondeterministic, is also explained, together with the proof of
how models of computation handle language recognition. Finally, the approach is
important when considering complexity, the problems that turn out undecidable,
showing thus the intrinsic limits of computation. This is an important resource
concerning formal languages, automata theory, and basic bounds of
computability.
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.
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.
This lecture
note from S R Engineering College offers a detailed introduction to key concepts
in the Theory of Computation. It begins with Properties of Binary
Operations, exploring fundamental mathematical operations and their
essential properties like associativity and commutativity. The section on
Concatenation Properties covers how strings can be joined and
the characteristics of such operations, including associativity and the identity
element. Finite Automata are thoroughly discussed, explaining
both deterministic and nondeterministic (NFA) models, and their role in
recognizing regular languages. The notes also cover Formal Languages,
categorizing them into regular, context-free, context-sensitive, and recursively
enumerable types based on complexity. Finally, the Pumping Lemma
is introduced as a critical tool for proving the non-regularity and
non-context-freeness of languages by demonstrating how strings in these
languages can be decomposed and manipulated.
This
is an all-inclusive course on computational theory provided in this online
resource by Wikiversity. It begins with Finite State Machines–their
definitions, operations, and minimization techniques. The notes also cover
closure and nondeterminism—how these properties may affect computational
models. Their discussion greatly involves the Pumping Lemma, proving language
property. The book also surveys Context-Free Languages and their connection to
Compilers and introduces Pushdown Machines emphatically and focuses on their
importance in parsing. It contains important material on the CYK algorithm for
parsing and the more basic problems of Undecidability. It also surveys Turing
Machines, the Halting Problem, and more general areas of Complexity Theory,
including Quantified Boolean Formulae, Savitch's Theorem, and Space Hierarchy.
The notes end with the Recursion Theorem, and it can be considered as a
landmark in the theoretical study of the science of computers.
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.