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Durham University

Faculty Handbook 2022-2023

Module Description

Please ensure you check the module availability box for each module outline, as not all modules will run each academic year.

Department: Computer Science

COMP2181: THEORY OF COMPUTATION

Type Open Level 2 Credits 20 Availability Available in 2022/23 Module Cap Location Durham

Prerequisites

  • COMP1081 Algorithms and Data Structures

Corequisites

  • None.

Excluded Combination of Modules

  • None.

Aims

  • To introduce students to: important models of computation and how they are related.
  • fundamental notions of computation such as 'computable' and 'efficiently computable'.
  • and the design and analysis of efficient algorithms.

Content

  • Models of computation
  • Basic computability theory
  • Algorithm design
  • Computational complexity

Learning Outcomes

Subject-specific Knowledge:
  • To have an understanding of different models of computation and their relevance to computer science.
  • To have an understanding of how algorithms can be used to solve fundamental problems within Computer Science.
Subject-specific Skills:
  • On completion of the module, students will be able to demonstrate:
  • an ability to use different models of computation in context of computer science
  • an ability to apply and analyze algorithms for fundamental problems within computer science
Key Skills:
  • On completion of the module, students will be able to:
  • extract an abstract computational model from a real world problem
  • distinguish between computationally tractable an intractable problems in computer science

Modes of Teaching, Learning and Assessment and how these contribute to the learning outcomes of the module

  • Lecturing demonstrates what is required to be learned and the application of the theory to practical examples.
  • Problem classes through practicals provide assessment (both formative and summative) to guide students in the correct development of their knowledge and skills.
  • The end of year examinations assess the knowledge acquired and the ability to use this knowledge to solve problems.

Teaching Methods and Learning Hours

Activity Number Frequency Duration Total/Hours
Lectures 44 2 per week 1 hour 44
Practicals 21 1 per week 2 hours 42
Preparation and Reading 114
Total 200

Summative Assessment

Component: Coursework Component Weighting: 34%
Element Length / duration Element Weighting Resit Opportunity
Practical work 100% Yes
Component: Examination Component Weighting: 66%
Element Length / duration Element Weighting Resit Opportunity
Examination 2 hours 100% Yes

Formative Assessment:

Example exercises given through the course.


Attendance at all activities marked with this symbol will be monitored. Students who fail to attend these activities, or to complete the summative or formative assessment specified above, will be subject to the procedures defined in the University's General Regulation V, and may be required to leave the University



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