Theory of Computing

Module overview

This module aims to provide a broad and stimulating introduction to the theory of computing.

Aims and Objectives

Learning Outcomes

Knowledge and Understanding

Having successfully completed this module, you will be able to demonstrate knowledge and understanding of:

The nature and examples of undecidable problems
The diagonalisation proof technique
The relationship between the regular, context-free and recursively enumerable classes of languages, and the state-machines that accept them
The complexity of algorithms and problems, and key complexity classes

Subject Specific Intellectual and Research Skills

Having successfully completed this module you will be able to:

Ascertain and prove whether or not a given language is context-free
Use polynomial-time reduction to reason about the complexity class of a problem
Analyse the complexity of a given algorithm or problem
Ascertain and prove whether or not a given language is regular
Use the reduction technique to show that a problem is undecidable

Learning and Teaching

Teaching and learning methods

The content of this module is delivered through lectures, the module website, directed reading, pre-recorded materials and tutorials. Students work on their understanding through a combination of independent study, preparation for timetabled activities, tutorials, and problem classes, along with formative assessments in the form of problem sheets.

Study time
Type	Hours
Tutorial	12
Wider reading or practice	50
Lecture	36
Follow-up work	18
Completion of assessment task	10
Preparation for scheduled sessions	6
Revision	18
Total study time	150

Resources & Reading list

Textbooks

M. Sipser (1997). Introduction to the Theory of Computation. PWS.

A.J.G. Hey (1996). Feynman Lectures on Computation. Addison Wesley.

A.K. Dewdney (2001). The (new) Turing Omnibus. Henry Holt.

N.D. Jones (1999). Computability and Complexity. MIT Press.

J. Barwise and J. Etchemendy (1993). Turing's World. Stanford.

D.C. Kozen (1999). Automata and Computability. Springer.

J. Gruska (1996). Foundations of Computing. Thomson.

D. Harel (1992). Algorithmics: The Spirit of Computing. Addison Wesley.

J. Hein (2002). Discrete Structures, Logic and Computability. Jones and Bartlett.

D. Cohen (1996). Introduction to Computer Theory. Wiley.

Assessment

Assessment strategy

This module is assessed by a combination of problem sheets and a final assessment in the form of a written examination.

Summative

This is how we’ll formally assess what you have learned in this module.

Breakdown
Method	Percentage contribution
Problem Sheets	10%
Examination	90%