Monash University

Leader: Associate Professor Bernd Meyer

Offered

Clayton First semester 2008 (Day)
Clayton Second semester 2008 (Day)
Sunway First semester 2008 (Day)

Synopsis

This unit introduces students to problem solving concepts and techniques fundamental to the science of programming. In doing this it covers problem specification, algorithmic design, analysis and implementation. Detailed topics include analysis of best-, average- and worst-case time- and space-complexity; introduction to numerical algorithms; recursion; advanced data structures such as heaps and B-trees; hashing; sorting algorithms; searching algorithms; graph algorithms; and numerical computing.

Objectives

Upon successful completion of this unit, students will have:

1. Understanding of a formal specification.;
2. Ability to create a formal specification for an informal problem;
3. Knowledge and understanding of algorithmic properties such as correctness, termination and complexity;
4. Ability to, given a non-trivial algorithm, formally prove certain properties, such as correctness and termination;
5. Ability, given a non-trivial algorithm, to determine its best- average- and worst-case, time- and space-complexity;
6. Knowldege and understanding of reasonably complex data structures such as minimum spanning trees, and Directed and Undirected, Weighted and Unweighted Graphs;
7. Ability to design and implement new non-trivial algorithms using complex data structures;
8. Knowledge of and ability to use algorithmic paradigms such as divide and conquer, greedy, dynamic programming and so on;
9. Ability to identify these paradigms in diverse algorithms;
10. Knowledge and understanding of the issues involved in implementing a non-trivial algorithm efficiently;

Upon successful completion of this unit, students will be able to carefully design and/or analyse the algorithms they are using in order to verify important properties such as correctness, termination, and complexity.

Upon successful completion of this unit, students will be able to:

1. Identify the key features of a brief informal problem description and abstract the underlying formal problem;
2. Create their own data structures;
3. Create a new algorithm to solve a new problem;
4. Make a formal argument about desirable properties of the solution;
5. Adapt an existing algorithm and/or data-structure where that is possible and appropriate;
6. Implement a non-trivial algorithm efficiently;

Upon successful completion of this unit, students will be able to make a 'formal argument' that an algorithm and/or data-structure has a given property, such as correctness, termination or complexity.

Assessment

Tutorials and practicals: 30%
Examination (3 hours): 70%.

Contact hours

4.5 x contact hrs/week

Prerequisites

One of CSE1303, FIT1008, FIT1015 and two of MAT1841, MAT1830, MTH1020 or MTH1030 or MTH112

Prohibitions

CSC2040, CSE2304, DGS2131, RDT2131