|Module Title||PROGRAM DESIGN, DATA STRUCTURES AND ALGORITHMS|
|Co-ordinator||Mr Richard C Shipman|
|Semester||Semester 2 (Taught over 2 semesters)|
|Other staff||Mr David J Smith|
|Course delivery||Lecture||44 lectures|
|Practical||Up to 20 x 1 hr (start in week 5)|
|Other||Workshop. Up to 4 x 1hr|
The module is also concerned with the reuse of software design patterns and frameworks, thereby reducing the need to build programs from first principles.
As well as providing a solid grounding in the major data structures and algorithms of Computer Science, the module stresses the development of problem solving skills through a number of programming worksheets.
An overview of the method of teaching and assessment, and a road-map of the topics to be covered and their relationships. Some basic concepts are introduced.
2. Program design issues - 4 Lectures
Explanation of design issues such as object-orientation and identification of components through case-study examples.
3. Design patterns and frameworks - 5 Lectures
An introduction to object-oriented design patterns and frameworks. Support for reuse. General concepts, representation and examples. How patterns may be implemented in Java.
4. Introduction to Complexity - 2 Lectures
O() notation, growth rates. Measurement of execution time of some example programs and estimation of their time complexity. P and NP.
5. Classes of Algorithm - 2 Lectures
An overview will be given on the different classes of algorithm; for example, divide and conquer and greedy algorithms.
6. Recursion - 2 Lectures
An introduction to recursive thinking. Examples of recursion.
7. Storing and Retrieving Data by Key (1) - 13 Lectures
This problem will be used to motivate the discussion of a wide variety of different implementation techniques. The features of some typical solutions will be related to the dimensions of the problem such as the volume of data to be handled, volatility and the operations required. Internal Storage: linear and binary searching. Linked representations; an introduction to hashing, binary search trees, AVL trees and heaps.
8. Storing and Retrieving Data by Key (2): External storage - 4 Lectures
Performance issues. Hashing and B-tree organisations. The Hashable class in Java.
9. Sorting - 4 Lectures
A comparison of divide and conquer, priority queue and address calculation based sorting algorithms. Performance characteristics of these algorithms will be discussed.
10. Representing Complex Relationships: Graphs - 7 Lectures
Some examples of greedy algorithms. Terminology and implementation considerations. A look at some graph-related problems such as: finding a route (shortest paths); planning a communications network (minimum spanning trees); network routing management (flow graphs); compiling a program or planning a project (topological sorting).
|Problem solving||This is inherent in both the formative practical work and the assessed coursework.|
|Research skills||The students will need to search for and use relevant technical information while completing practical and assessed coursework.|
|Communication||Written skills will be needed to complete supporting documents to accompany assessed coursework.|
|Improving own Learning and Performance||See 2 above.|
|Information Technology||The whole module concerns this area.|
|Application of Number||Yes, particularly in algorithm analysis.|
|Personal Development and Career planning||Carefully time management will be needed as so to enable students to complete coursework etc.|
|Subject Specific Skills||Yes. See module title and content.|
This module is at CQFW Level 5