Undergraduate Programme and Module Handbook 2020-2021 (archived)
Module COMP3507: COMPUTATIONAL COMPLEXITY
Department: Computer Science
COMP3507: COMPUTATIONAL COMPLEXITY
| Type | Open | Level | 3 | Credits | 10 | Availability | Available in 2020/21 | Module Cap | None. | Location | Durham |
|---|
Prerequisites
- COMP2181 Theory of Computation
Corequisites
- None
Excluded Combination of Modules
- None
Aims
- The aim of the module is to equip students with the ability to ability to formalise and reason about the complexity of computational problems as well as to identify barriers to efficient computations.
Content
- The content will be chosen from the following topics:
- Time complexity and space complexity of computational problems
- Complexity of optimisation and approximation
- Parameterised complexity
- Circuit complexity
- Complexity and cryptography
- Complexity of randomised computation
- Descriptive complexity
Learning Outcomes
Subject-specific Knowledge:
- 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 ways to measure and reason about the complexity of computation;
- a knowledge about various important problem solving paradigms in the broad area of algorithms and complexity.
Subject-specific Skills:
- On completion of this module, students will be able to demonstrate:
- an ability to apply techniques and methods to evaluate the complexity of fundamental computational problems;
- an ability to conduct review and self-study to further their knowledge beyond the taught material.
Key Skills:
- 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 | 22 | 2 per week | 1 hour | 20 | |
| Preparation and reading | 80 | ||||
| Total | 100 |
Summative Assessment
| Component: Examination | Component Weighting: 100% | ||
|---|---|---|---|
| Element | Length / duration | Element Weighting | Resit Opportunity |
| Examination | 2 hours | 100% | No |
Formative Assessment:
Example formative exercises given during the course. Additional revision lectures may be arranged in the module 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