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:
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, Eular tours.
Further algorithmic problems on graphs: minimum spanning trees, shortest path problems, matching problems.
Planar graphs and their properties. Eular's formula, planar separateor 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:
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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.
Communication: presentation skills, focusing on mathematicalstyle presentation (students will have to prepare a short presentation describing some of the topics from the module).
Type  Required 

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  

Coursework  20%  
There will be 3 marked problem sets, each worth 10 points. The overall mark for this assessment will be calculated as the average of these elements. 

Oncampus Examination  80%  
CS254 exam ~Platforms  AEP

Weighting  Study time  

Online Examination  100%  
CS254 resit examination ~Platforms  AEP

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:
This module is Option list C for: