Logo

Mathematical Foundations of Computer Science

Small book cover: Mathematical Foundations of Computer Science

Mathematical Foundations of Computer Science
by

Publisher: Duke University

Description:
These lecture notes present an introduction to theoretical computer science including studies of abstract machines, the language hierarchy from regular languages to recursively enumerable languages, noncomputability and complexity theory.

Home page url

Download or read it online for free here:
Download link
(multiple PDF, PS files)

Similar books

Book cover: How to think like a Computer Scientist (C++ Version)How to think like a Computer Scientist (C++ Version)
by
This book teaches you to think like a computer scientist - to combine the best features of mathematics, natural science, and engineering, to use formal languages to denote ideas, to observe the behavior of complex systems, form hypotheses, etc.
(17211 views)
Book cover: Concrete Abstractions: An Introduction to Computer Science Using SchemeConcrete Abstractions: An Introduction to Computer Science Using Scheme
by - Course Technology
The book Concrete Abstractions covers the programming and data structures basics. It will give first-time computer science students the opportunity to not only write programs, but to prove theorems and analyze algorithms as well.
(14453 views)
Book cover: A Balanced Introduction to Computer ScienceA Balanced Introduction to Computer Science
by - Prentice Hall
The book covers concepts in computing that are most relevant to the beginning student, including computer terminology, the Internet and World Wide Web, the history of computing, the organization and manufacture of computer technology, etc.
(26946 views)
Book cover: Building Blocks for Theoretical Computer ScienceBuilding Blocks for Theoretical Computer Science
by - University of Illinois, Urbana-Champaign
This book provides a survey of basic mathematical objects, notation, and techniques useful in later computer science courses. It gives a brief introduction to some key topics: algorithm analysis and complexity, automata theory, and computability.
(7455 views)