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COMP4087: ADVANCED ALGORITHMS

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Type	Open
Level	4
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

To give students a deeper knowledge of algorithmic solutions for typical computer science problems.
To extend the students' knowledge of the latest advances in understanding the limits of computation and the ways of coping with computational hardness.

Content

Algorithms: approximation, exact, fixed parameter tractable, polynomial
Input restrictions: hereditary and intersection graph classes
Graph width
Graph containment relations
Graph reconfiguration

Learning Outcomes

Subject-specific Knowledge:

On completion of the module, students will be able to demonstrate:
a comprehensive understanding of how the theory of computation is applied in the design of algorithms
a critical evaluation of different approaches to the algorithmic solution for computationally hard problems
a critical awareness of some of the latest advances in research on theoretical aspects of computation

Subject-specific Skills:

On completion of the module, students will be able to demonstrate:
an ability to critically apply notions from the theory of computation
an ability to choose and evaluate the best way to tackle computationally hard problems
an ability to judge research on the cutting edge of the theory of computation

Key Skills:

On completion of the module, students will be able to demonstrate:
an ability to abstract and solve problems
an ability to learn independently
an ability to communicate technical information

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

Lectures enable the students to learn new material relevant to the theory of computation
Formative homework exercises identify areas where further independent research could 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	24	2 per week	1 hour	24
preparation and reading				76
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 are given during the course. Additional revision lectures may be arranged in the module's lecture slots in the 3rd term.

More information

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