Undergraduate Programme and Module Handbook 2017-2018 (archived)
Module COMP3391: THEORETICAL COMPUTER SCIENCE III
Department: Computer Science
COMP3391:
THEORETICAL COMPUTER SCIENCE III
Type |
Open |
Level |
3 |
Credits |
20 |
Availability |
Available in 2017/18 |
Module Cap |
|
Location |
Durham
|
Prerequisites
Corequisites
Excluded Combination of Modules
Aims
- The aim of the module is to equip students with the ability to use techniques and methods to efficiency solve fundamental computational problems as well as to identify barriers to efficient solutions.
Content
- There are four strands:
- Advanced Algorithms. Topics
will be chosen from sorting and searching, string problems, approximation and randomised algorithms.
- Complexity and Approximability. Topics
will be chosen from space complexity and complexity of optimisation and approximation.
- Algorithmic Game Theory. Topics
will be chosen from games on graphs (congestion games, selfish routing), social choice and algorithmic mechanism design.
- Coding Theory. Topics
will be chosen from entropy, channel capacity, rate-distortion theory and Kolmogorov complexity.
Learning Outcomes
- On completion of this module, students will be able to demonstrate:
- an understanding of the inherent limitations of computation through appreciation of the topic areas;
- an appreciation of different parameters and models of computation relevant to the efficient solution of computational problems;
- an understanding of how to measure, transfer and handle information;
- a knowledge about various important problem solving paradigms in the broad area of algorithms and complexity.
- On completion of this module, students will be able to demonstrate:
- an ability to apply techniques and methods from the relevant topics to tackle fundamental computational problems ;
- an ability to conduct review and self-study to further their knowledge beyond the taught material.
- On completion of this module, students will be able to demonstrate:
- an ability to think critically;
- an ability to work with abstract problems;
- an ability to undertake general problem solving.
Modes of Teaching, Learning and Assessment and how these contribute to
the learning outcomes of the module
- Lectures provide the material required to be learned and the application of the theory to practical examples.
- Coursework identify areas where further independent study should be conducted.
- Summative assessments test the knowledge acquired and the students' ability to use this knowledge to solve complex problems.
Teaching Methods and Learning Hours
Activity |
Number |
Frequency |
Duration |
Total/Hours |
|
lectures |
44 |
2 per week |
1 hour |
44 |
|
problems classes |
8 |
4 in term 1, 4 in term 2 |
1 hour |
8 |
■ |
preparation and reading |
|
|
|
148 |
|
Total |
|
|
|
200 |
|
Summative Assessment
Component: Examination |
Component Weighting: 66% |
Element |
Length / duration |
Element Weighting |
Resit Opportunity |
Examination |
2 hours |
100% |
No |
Component: Coursework |
Component Weighting: 34% |
Element |
Length / duration |
Element Weighting |
Resit Opportunity |
Practical work |
|
100% |
No |
Example formative exercises given during the course. Additional revision lectures may be arranged in the modules lecture slots in the 3rd term.
■ 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