COMP11212 Fundamentals of Computation syllabus 2021-2022

COMP11212 Fundamentals of Computation

Level 1
Credits: 10
Enrolled students: pending

Course leader: Sean Bechhofer

Additional staff: view all staff

Requisites

• 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

Timetable

Semester	Event	Location	Day	Time	Group
Sem 2 w20-27,31-33	Lecture	MEC Hall 2.040 Lecture Theatre	Thu	10:00 - 11:00	-
Sem 2 w20-27,31-33	Lecture	MEC Hall 2.040 Lecture Theatre	Mon	11:00 - 12:00	-
Sem 2 w21-27,31-33	Examples	Collab	Wed	09:00 - 10:00	W
Sem 2 w21-27,31-33	Examples	Collab	Tue	09:00 - 10:00	M+X
Sem 2 w21-27,31-33	Examples	Collab	Tue	10:00 - 11:00	Y
Sem 2 w21-27,31-33	Examples	2.19	Tue	14:00 - 15:00	Z
Sem 2 w21-27,31-33	Examples	Collab	Tue	16:00 - 17:00	V

Overview

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.

Aims

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?

Syllabus

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

Lectures

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

Additional notes

Course unit materials

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