Foundations of Computer Science

Introduces the principles of data structures and algorithms. Emphasises the algorithmic side of programming, focusing on problem-solving rather than on hardware-level bits and bytes.

**Publication date**: 31 Dec 2000

**ISBN-10**:
n/a

**ISBN-13**:
n/a

**Paperback**:
155 pages

**Views**: 34,228

**Type**: Lecture Notes

**Publisher**:
n/a

**License**:
n/a

**Post time**: 16 Oct 2006 12:49:57

Foundations of Computer Science

Introduces the principles of data structures and algorithms. Emphasises the algorithmic side of programming, focusing on problem-solving rather than on hardware-level bits and bytes.

Document Excerpts:

These are the lecture notes for the Foundations of Computer Science course at the Computer Laboratory, University of Cambridge.

The principal aim of this course is to present the basic principles of programming. As the introductory course of the Computer Science, it caters to students from all backgrounds. To those who have had no programming experience, it will be comprehensible; to those experienced in languages such as C, it will attempt to correct any bad habits that they have learnt.

A further aim is to introduce the principles of data structures and algorithms. The course will emphasise the algorithmic side of programming, focusing on problem-solving rather than on hardware-level bits and bytes. Accordingly it will present basic algorithms for sorting, searching, etc., and discuss their efficiency using O-notation. Worked examples (such as polynomial arithmetic) will demonstrate how algorithmic ideas can be used to build efficient applications.

The course will use a functional language (ML). ML is particularly appropriate for inexperienced programmers, since a faulty program cannot crash. The course will present the elements of functional programming, such as curried and higher-order functions. But it will also discuss traditional (procedural) programming, such as assignments, arrays, pointers and mutable data structures.

These are the lecture notes for the Foundations of Computer Science course at the Computer Laboratory, University of Cambridge.

The principal aim of this course is to present the basic principles of programming. As the introductory course of the Computer Science, it caters to students from all backgrounds. To those who have had no programming experience, it will be comprehensible; to those experienced in languages such as C, it will attempt to correct any bad habits that they have learnt.

A further aim is to introduce the principles of data structures and algorithms. The course will emphasise the algorithmic side of programming, focusing on problem-solving rather than on hardware-level bits and bytes. Accordingly it will present basic algorithms for sorting, searching, etc., and discuss their efficiency using O-notation. Worked examples (such as polynomial arithmetic) will demonstrate how algorithmic ideas can be used to build efficient applications.

The course will use a functional language (ML). ML is particularly appropriate for inexperienced programmers, since a faulty program cannot crash. The course will present the elements of functional programming, such as curried and higher-order functions. But it will also discuss traditional (procedural) programming, such as assignments, arrays, pointers and mutable data structures.

Tweet

About The Author(s)

Lawrence C. Paulson is Professor of Computational Logic in Computer Laboratory at the University of Cambridge. His research concerns automated theorem proving and its applications: development of Isabelle, with emphasis on automation; MetiTarski, an automatic prover for the elementary functions; formalising mathematics, including Gödel's incompeteness theorems and constructible universe; and proving the correctness of security protocols;

Book Categories

Computer Science
Introduction to Computer Science
Introduction to Computer Programming
Algorithms and Data Structures
Artificial Intelligence
Computer Vision
Machine Learning
Neural Networks
Game Development and Multimedia
Data Communication and Networks
Coding Theory
Computer Security
Information Security
Cryptography
Information Theory
Computer Organization and Architecture
Operating Systems
Image Processing
Parallel Computing
Concurrent Programming
Relational Database
Document-oriented Database
Data Mining
Big Data
Data Science
Digital Libraries
Compiler Design and Construction
Functional Programming
Logic Programming
Object Oriented Programming
Formal Methods
Software Engineering
Agile Software Development
Information Systems
Geographic Information System (GIS)

Mathematics
Mathematics
Algebra
Abstract Algebra
Linear Algebra
Number Theory
Numerical Methods
Precalculus
Calculus
Differential Equations
Category Theory
Proofs
Discrete Mathematics
Theory of Computation
Graph Theory
Real Analysis
Complex Analysis
Probability
Statistics
Game Theory
Queueing Theory
Operations Research
Computer Aided Mathematics

Supporting Fields
Web Design and Development
Mobile App Design and Development
System Administration
Cloud Computing
Electric Circuits
Embedded System
Signal Processing
Integration and Automation
Network Science
Project Management

Operating System
Programming/Scripting
Ada
Assembly
C / C++
Common Lisp
Forth
Java
JavaScript
Lua
Microsoft .NET
Rexx
Perl
PHP
Python
R
Rebol
Ruby
Scheme
Tcl/Tk

Miscellaneous
Sponsors