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This is an archived syllabus from 2020-2021

COMP11212 Fundamentals of Computation syllabus 2020-2021

COMP11212 Fundamentals of Computation

Level 1
Credits: 10
Enrolled students: 388

Course leader: Sean Bechhofer

Additional staff: view all staff


  • Co-Requisite (Compulsory): COMP11120

Additional requirements

  • Students who are not from the School of Computer Science must have permission from both Computer Science and their home School to enrol.

Assessment methods

  • 80% Written exam
  • 20% Coursework
Sem 2 ONLINE ACTIVITY Thu 10:00 - 11:00 -
Sem 2 w20-26,29-31 INDEPENDENT STUDY Mon 11:00 - 12:00 -
Sem 2 w21-26,29-32 ONLINE Examples Tue 09:00 - 10:00 Y
Sem 2 w21-26,29-32 ONLINE Examples Tue 11:00 - 12:00 M+W
Sem 2 w21-26,29-32 ONLINE Examples Fri 14:00 - 15:00 Z
Sem 2 w21-26,29-32 ONLINE Examples Tue 16:00 - 17:00 X


The building of real-life computing systems, e.g. mobile phone, tv/video remote control, internet shopping, air-traffic control, internet banking, etc., is always a complex task. Mistakes can be very annoying, costly and sometimes life threatening. Methods and techniques to support the building and understanding of such systems are essential. This course unit provides an introduction to the basic computer science ideas underlying such methods. It is also a part of, and an introduction to, the Modelling and Rigorous Development theme.

This course unit detail provides the framework for delivery in 20/21 and may be subject to change due to any additional Covid-19 impact.  Please see Blackboard / course unit related emails for any further updates.


This course unit provides a first approach to answering the following questions. What methods are there that can help understanding complicated systems or programs? How can we make sure that a program does what we intend it to do? How do computers go about recognizing pieces of text? If there are two ways of solving the same problem, how can we compare them? How do we measure that one of them gives the solution faster? How can we understand what computers can do in principle, and are there problems that are not solvable by a computer?


There are two groups of topics covered. One of the lectures will be an introduction to the course unit, and one is reserved for revision. That leaves 10 lectures for each part.

The first part (10 lectures) is concerned with expressing particular strings, and collections of strings, and here we will introduce the methods by which a computer goes about it. The ability to recognize key strings (such as programming constructs or variable names) are, for example, required in every compiler, but they are also used by search engines such as Google.The formalisms introduced include finite state automata, regular expressions (most often used in pattern matching), (regular) grammars. The emphasis is on students being able to use these formalisms to solve problems.

The second half of the course (10 lectures) provides an introduction to the topics of complexity, correctness and computability. There are four big topics:

                • the WHILE programming language

                • asymptotic complexity

                • partial and full program correctness

                • computability

Teaching methods


22 in total, 2 per week

Examples classes

1 per week (starting in week 2)

Feedback methods

Students present their solutions to set exercises once a week in examples classes. They receive oral feedback to their solutions, and have the opportunity to improve some of their original answers for further feedback.

Study hours

  • Assessment written exam (2 hours)
  • Lectures (24 hours)
  • Practical classes & workshops (11 hours)

Employability skills

  • Analytical skills
  • Oral communication
  • Problem solving

Learning outcomes

On successful completion of this unit, a student will be able to:

  • Describe formal languages using a variety of mechanisms.   
  • Define classes of languages and demonstrate translations between those classes.
  • State key properties of classes of languages and determine when those properties hold.
  • Define models of computation and use those models to demonstrate what can and cannot be computed.

Reading list

Introduction to the Theory of ComputationMichael Sipser113318779X; 9781133187790; 9781133187813Cengage Learning2013
Logic in computer science : modelling and reasoning about systems Huth, Michael, 1962-052154310XCambridge University Press2004.
Introduction to automata theory, languages, and computation Hopcroft, John E., 1939-9781292056166Pearson Education©2014.
Introduction to the theory of computation Sipser, Michael.9781133187813Cengage Learningc2013.

Additional notes

Course unit materials

Links to course unit teaching materials can be found on the School of Computer Science website for current students.