2011/12 Undergraduate Module Catalogue

COMP1640 Modelling, Analysis and Algorithm Design

20 creditsClass Size: 80

Module manager: Dr Vania Dimitrova
Email: V.G.Dimitrova@leeds.ac.uk

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

Year running 2011/12

This module is not approved as an Elective

Objectives

On completion of this module, students should be able to:

- apply the basic techniques of statistical data analysis;
- understand the floating point data representation and the associated problems;
- understand the basic principles of ER modelling;
- understand the concept of the computational model and design a model for a simple business and scientific application;
- understand the basic techniques for requirements investigation, system analysis and design;
- understand the operation of iterative and recursive algorithms;
- understand the importance of algorithm analysis in computing;
- analyse the time complexity of several types of algorithms;
- understand a range of algorithm design techniques and general problem solving strategies;
- appreciate the importance of data structures and their implementation.

Syllabus

- Data and its analysis: statistical analysis of qualitative data, floating point data representation, round-off computation errors and their propagation.

- Data modelling: introduction to the entity-relationship model.

- Model building and interpreting in mathematical programming, model classification (linear/nonlinear, deterministic/stochastic, static/dynamic, discrete/continuous).

- Business process modelling.

- Algorithms and their analysis: iterative algorithms, recursive algorithms, worst-case analysis of algorithms.

- Algorithm design techniques: brute force, divide-and-conquer, decrease-and-conquer, transform-and-conquer (Gaussian elimination), dynamic programming, greedy technique.

- Simple data structures: arrays, lists, stacks, queues and heaps.

Teaching methods

Delivery type	Number	Length hours	Student hours
Example Class	20	1.00	20.00
Class tests, exams and assessment	1	2.00	2.00
Class tests, exams and assessment	1	3.00	3.00
Lecture	44	1.00	44.00
Private study hours			131.00
Total Contact hours			69.00
Total hours (100hr per 10 credits)			200.00

Private study

- Taught session preparation: 36 hours
- Taught session follow-up: 36 hours
- Self-directed study: 14 hours
- Assessment activities: 45 hours.

Opportunities for Formative Feedback

Attendance and formative assessment

Methods of assessment

Exams

Exam type	Exam duration	% of formal assessment
Standard exam (closed essays, MCQs etc)	3 hr 00 mins	100.00
Standard exam (closed essays, MCQs etc)	2 hr 00 mins	0.00
Total percentage (Assessment Exams)		100.00

Normally resits will be assessed by the same methodology as the first attempt, unless otherwise stated

Reading list

The reading list is available from the Library website

Last updated: 04/10/2011

Disclaimer

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