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2024/25 Undergraduate Module Catalogue

COMP1870 Theoretical Foundations of Computer Science I

40 creditsClass Size: 350

Module manager: Prof Dillon Mayhew

Taught: Semesters 1 & 2 (Sep to Jun) View Timetable

Year running 2024/25


COMP1860Building our Digital World: Computer Systems & Architecture

This module is not approved as a discovery module

Module summary

Computer Science, at its foundation, is a mathematical and engineering discipline. This module lays the foundation of the mathematical and theoretical concepts in Computer Science and forms part of the core of the Computer Science curriculum. This module equips students with a set of core knowledge and skills enabling students to view real world problems algorithmically and supports them to apply rigorous mathematical approaches to solve them.


To develop an appreciation of, and familiarity with, mathematical concepts and their application in computer science. To equip students with the appropriate problem-solving techniques and transferable skills to tackle real world problems computationally.

Learning outcomes
On successful completion of this module a student will have demonstrated the ability to:
1. recall and apply definitions and theorems to well-specified problems relating to topics relevant to Computer Science. (C1, M1)
2. effectively communicate complex topics at the foundation of Computer Science to technical and non-technical audiences. (C17, M17)
3. select and apply appropriate computational and analytical techniques to model and solve complex real-world problems. (C3, M3)
4. select and interpret relevant information from multiple sources to solve complex real-world problems. (C4, M4)
5. identify and analyse ethical concerns when applying techniques to model real world problems and make reasoned decisions informed by ethical frameworks and codes of conduct. (C8, M8)
6. effectively use appropriate computing machinery and technologies to investigate complex real-world problems, identifying limitation where they occur. (C12, M12, C13, M13)
7. reflect on their level of mastery of subject knowledge and skills and plan for personal development. (C18, M18)

Skills Learning Outcomes
a) Technical,
b) Communication,
c) Teamwork,
d) Time management,
e) Problem solving,
f) Active learning,
g) Reflection,
h) Critical thinking,
g) Ethics.


• Data structures
- Tuples, Arrays, stacks, queues, lists, trees, maps, graphs, sets
• Basic algorithms
- Searching
- Sorting
- Solving non-linear equations
- Graph algorithms
• Complexity
- Big-O, Big-Omega, and Big-Theta notation
- Models of computation
- Empirical measurements of performance
• Calculus
- Sequences, series and limits
- Derivatives
- Integration
- Applications in computer science
• Linear algebra
- Vectors: definitions, vector operations, geometric interpretation, angles
- Matrices: definitions, transformations
• Probability
- sample spaces, events, probability, conditional probability, Bayes’ rule
- Discrete random variables and distributions
- Continuous random variables and distributions
- Conditional distributions and expectation
• Proof techniques
• Discrete mathematics
- Sets, relations, functions, cardinality
- Counting
- Modular arithmetic
- Logic
- Graph theory

Methods of Assessment

We are currently refreshing our modules to make sure students have the best possible experience. Full assessment details for this module are not available before the start of the academic year, at which time details of the assessment(s) will be provided.

Assessment for this module will consist of:

1 x Coursework
1 x Exam
1 x In-Class Test

Opportunities for Formative Feedback

Students will have an opportunity for continuous feedback on all components of the portfolio via tutorials, personal tutorials and via additional support activities. Students will have regular portfolio checkpoints to ensure students are progressing towards the assessment objectives.

Reading list

The reading list is available from the Library website

Last updated: 09/05/2024


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