This module is concerned with studying properties of graphs and digraphs from an algorithmic perspective. This module is only available to students in the second year of their degree and is not available as an unusual option to students in other years of study.
This module is concerned with studying properties of graphs and digraphs from an algorithmic perspective. The focus is on understanding basic properties of graphs that can be used to design efficient algorithms. The problems considered will be typically motivated by algorithmic/computer science/IT applications.
This is an indicative module outline only to give an indication of the sort of topics that may be covered. Actual sessions held may differ.
Typical topics include the following. Introduction to graphs: undirected graphs, directed graphs, weighted graphs, graph representation and special classes of graphs (trees, planar graphs etc.). Applications of graphs (in telecommunications, networking etc.). Basic algorithmic techniques for graph problems: graph traversals (DFS and BFS), topological sorting, Euler tours. Further algorithmic problems on graphs: minimum spanning trees, shortest path problems, matching problems. Planar graphs and their properties. Euler's formula, planar separator theorem and their algorithmic applications. Further optimization problems on graphs including graph colouring and graph questions in distributed systems. Discussing practical applications of graphs and efficient algorithms for such practical problems. Approximation algorithms and heuristic algorithms. Applications to searching in massive graphs (e.g. page ranking); use of structural properties and algebraic properties.
By the end of the module, students should be able to:
Please see Talis Aspire link for most up to date list.
View reading list on Talis Aspire
Acquiring basic knowledge in the new area (of algorithmic graph theory), including learning the key concepts of mathematical rigour in the analysis of graph algorithms, of the proofs of correctness of algorithms, and of the efficiency of algorithms. An important part of the module will be to focus on mathematical properties of graphs and networks, as a tool to the design of better algorithms.
Critical thinking and creativity.
Type | Required |
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Lectures | 30 sessions of 1 hour (20%) |
Seminars | 9 sessions of 1 hour (6%) |
Private study | 111 hours (74%) |
Total | 150 hours |
Private study and independent learning include:
No further costs have been identified for this module.
You do not need to pass all assessment components to pass the module.
Students can register for this module without taking any assessment.
Weighting | Study time | |
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Problem set 1 | 10% | |
This is the first of two marked problem sets. This assessment is eligible for self-certification (extension). |
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Problem set 2 | 10% | |
This is the second of two marked problem sets. This assessment is eligible for self-certification (extension). |
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In-person Examination | 80% | |
CS254 exam
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Weighting | Study time | |
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In-person Examination - Resit | 100% | |
CS254 resit examination
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Feedback on problem sets in seminars.
This module is Core for:
This module is Optional for:
This module is Option list A for:
This module is Option list B for: