Module Search

COMP3507: COMPUTATIONAL COMPLEXITY

Please ensure you check the module availability box for each module outline, as not all modules will run in each academic year. Each module description relates to the year indicated in the module availability box, and this may change from year to year, due to, for example: changing staff expertise, disciplinary developments, the requirements of external bodies and partners, and student feedback. Current modules are subject to change in light of the ongoing disruption caused by Covid-19.

Type	Open
Level	3
Credits	10
Availability	Available in 2023/24
Module Cap	None.
Location	Durham
Department	Computer Science

Prerequisites

COMP2181 Theory of Computation

Corequisites

None

Excluded Combinations 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
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.

More information

If you have a question about Durham's modular degree programmes, please visit our FAQ webpages, Help page or our glossary of terms. If you have a question about modular programmes that is not covered by the FAQ, or a query about the on-line Undergraduate Module Handbook, please contact us.

Prospective Students: If you have a query about a specific module or degree programme, please Ask Us.

Current Students: Please contact your department.