Module Identifier MA28010  
Module Title MATHEMATICS FOR SOFTWARE ENGINEERING  
Academic Year 2000/2001  
Co-ordinator Dr J M Pearson  
Semester Semester 2 (Taught over 2 semesters)  
Other staff Mr D A Jones  
Mutually Exclusive Only available as part of a degree course in the Computer Science Department  
Course delivery Lecture   22 x 1 hour lectures  
  Workshop   10 x 1 hour workshops  
Assessment Exam   2 Hours (written examination)   100%  
  Resit assessment   2 Hours (written examination)   100%  

General description
Like other branches of science and engineering, Software engineering and Computer Science rely on mathematics for techniques to model the real world both in its physical, and in its more abstract, aspects. The mathematics taught in this module provides the basis for understanding how numbers are stored and manipulated, explains basic coordinate geometry, statistical techniques and the solution of recurrence relations. Practical applications of the material covered will be found in modules on graphics, robotics, programming languages and quantitative aspects of software engineering.

Aims
The aim of this module is to give students the mathematical skills needed to handle the quantitative aspects of software engineering.

Learning outcomes
On completion of this module, a student should be able to:

Syllabus
The presentation of the mathematical ideas will be directed to their use in computing.
1. Numbers; rational and irrational. Computer representation of numbers and floating point operations.
2. Coordinate geometry; lines, planes, conics; translation, rotation, shearing, scaling.
3. Summarising data. Histograms. Five number summaries. Box and whisker plots. Shapes of distributions. Graphical test for symmetry (normality). Binomial experiments and large sample behaviour. The Poisson distribution as a model for randomness. Quick and graphical tests for the Poisson distribution. Waiting times and the exponential distribution.
4. Solution of first and second order linear recurrence relations; some examples of non-linear equations. Application to the assessment of time complexity of algorithms.

Reading Lists
Books
** Supplementary Text
J H Conway & J Guy. The Book of Numbers.
J H Mathews. Numerical Methods for Mathematics, Science, Engineering.
H Thomas. Mathematical Models.
P J McKerrow. Introduction to Robotics.
R L Finney & G B Thomas. (1994) Calculus. 2nd edition. Addison-Wesley
A V Aho, J E Hopcroft & J D Ullman. Data Structures and Algorithms.
J T Sandefur. Discrete Dynamical Systems, Theory and Applications.