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Theory 1: Mathematical Foundations of Computer Science - COM00013C

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  • Department: Computer Science
  • Credit value: 20 credits
  • Credit level: C
  • Academic year of delivery: 2022-23

Module summary

Mathematical Foundations of Computer Science

Module will run

Occurrence Teaching period
A Autumn Term 2022-23

Module aims

Students will be introduced to the key discrete mathematics concepts that are the foundation of computer science. Students will be introduced to propositional and predicate logic, set theory, combinatorics, functions and relations and graph theory. Students will be introduced to the mathematical foundations, and will be able to identify the application of these concepts in real-world examples. Students will be introduced to a variety of proof techniques that will be used throughout their degree programme.

Module learning outcomes

T101

Define, read and apply mathematical notations for purposes of describing mathematical concepts from across discrete mathematics including: propositional and predicate logic, set theory, combinatorics, functions and relations, and graph theory.

T102

Formulate definitions and examples of concepts across discrete mathematics

T103

Apply a variety of techniques to identify whether logical expressions are true or false, valid or invalid or equivalent to one another.

T104

Select appropriate techniques to prove properties about discrete mathematics concepts.

T105

Construct counterexamples to refute claims about discrete mathematics concepts.

T106

Select and construct appropriate proof techniques to prove a variety of different types of problems in discrete mathematics.

T107

Describe and use the basic concepts of discrete probability to describe events.

T108

Apply logical statements to describe real-world logical problems in relation to computer science

T109

Identify and provide examples of real-world application of sets to computer science problems

T110

Describe and apply a variety of concepts and techniques about functions and relations as they apply to computer science.

T111

Formally define and illustrate by example graphs of different graph classes, their properties and special cases of: undirected, directed, cyclic, edge labelled, weighted, directed acyclic and disconnected graphs.

T112

Model a variety of real-world problems in computer science using appropriate forms of graphs and trees,

Indicative assessment

Task % of module mark
Online Exam -less than 24hrs (Centrally scheduled) 100

Special assessment rules

None

Indicative reassessment

Task % of module mark
Online Exam -less than 24hrs (Centrally scheduled) 100

Module feedback

Feedback is provided through work in practical sessions, and after the final assessment as per normal University guidelines.

Indicative reading

** Dean N., The Essence of Discrete Mathematics, Prentice Hall, 1997

** Haggarty R., Discrete Mathematics for Computing, Addison Wesley, 2002

** Truss J., Discrete Mathematics for Computer Scientists, Addison Wesley, 1999

** Gordon H., Discrete Probability, Springer, 1997

* Solow D., How to Read and Do Proofs, Wiley, 2005


The information on this page is indicative of the module that is currently on offer. The University constantly explores ways to enhance and improve its degree programmes and therefore reserves the right to make variations to the content and method of delivery of modules, and to discontinue modules, if such action is reasonably considered to be necessary. In some instances it may be appropriate for the University to notify and consult with affected students about module changes in accordance with the University's policy on the Approval of Modifications to Existing Taught Programmes of Study.