The University of Southampton
Courses

COMP2210 Theory of Computing

Module Overview

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

Aims and Objectives

Module Aims

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

Learning Outcomes

Knowledge and Understanding

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

  • The relationship between the regular, context-free and recursively enumerable classes of languages, and the state-machines that accept them
  • The nature and examples of undecidable problems
  • The diagonalisation proof technique
  • The time and space complexity of algorithms and problems
  • The complexity classes P and NP together with examples of NP-complete problems
  • The complexity class PSPACE together with examples of PSPACE-complete problems
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 regular
  • Ascertain and prove whether or not a given language is context-free
  • Use the reduction technique to show that a problem is undecidable
  • Analyse the complexity of a given algorithm or problem
  • Use polynomial-time reduction to reason about the complexity class of a problem

Syllabus

Automata theory - Finite state automata, regular expressions and regular languages - The pumping lemma for regular languages - Closure properties of regular languages - The Myhill-Nerode theorem - Context-free grammars and pushdown automata - Closure properties of context-free languages - The pumping lemma for context-free languages Computability theory - Turing machines, recursively enumerable and recursive languages - Church-Turing thesis - Limitations of algorithms: universality, the halting problem and undecidability Computational complexity theory - Complexity of algorithms and of problems - Complexity classes P, NP, PSPACE - Polynomial-time reduction - NP-Completeness and Cook's theorem - PSPACE-Completeness

Learning and Teaching

TypeHours
Preparation for scheduled sessions18
Completion of assessment task15
Lecture36
Follow-up work18
Wider reading or practice41
Revision10
Tutorial16
Total study time154

Resources & Reading list

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

Hey AJG (1996). Feynman Lectures on Computation. 

Cohen D (1996). Introduction to Computer Theory. 

Gruska J (1996). Foundations of Computing. 

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

Dexter C. Kozen (1999). Automata and Computabilty. 

Jones ND (1997). Computability and Complexity. 

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

Dewdney AK (2001). The (new) Turing Omnibus. 

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

Assessment

Summative

MethodPercentage contribution
Examination  (1 hours) 30%
Test 70%

Referral

MethodPercentage contribution
Examination 100%

Repeat Information

Repeat type: Internal & External

Linked modules

Pre-requisites: COMP1201 (Algorithmics) AND COMP1215 (Foundations Of Computer Science)

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