The Graduate Diploma of Computing and the Masters of Applied Information Technology have been reviewed and restructured jointly by all schools involved in teaching it. The changes have been designed to ensure smoother movement of students between the Graduate Diploma of Computing and the MAIT, and in light of changed immigration rules. This unit is being introduced for this revised program.

GCO3512 Data Structures and Algorithms is included in the program as an elective unit to replace the unit GCO9807 Data Structures and Algorithms. The GSCIT Education Committee supports this coding since the content and difficulty of the unit is equivalent to other third year units, and it has two Java programming units as prerequisites.

Students in the Bachelor of IT with a major in System Development will continue to take the second level coded version GCO2817 until the BIT can be reorganised to accommodate the third level offering of this unit.

This unit has been updated as part of a 2009 review and comparison of data with current Handbook, Syllabus + and Callista data.

At the completion of this unit students will have -

• the ability to analyse simple algorithms to work out an order of magnitude estimate of running time and space;
• familiarity with some of the most common data structures: stacks, queues, lists, priority queues, tables, sets, collections;
• ability to implement these data structures using various common data representations: arrays, linked lists, heaps, trees (including balanced trees), hashing;
• the ability to evaluate which implementation would be most appropriate for a given data structure and application;
• the ability to apply the same principles used in implementing the common data structures to implement other data structures;
• the ability to design and implement new data structures;
• an understanding of some more advanced algorithms in areas such as: graph theory (shortest path etc), pattern searching, data compression, (precise selection of advanced algorithms will vary from year to year);
• an ability to design new algorithms to solve new problems;
• an enjoyment of programming as an intellectual exercise;
• an appreciation of the elegance of certain data structures and algorithms as a form of art;
• an interest in understanding how data structures and algorithms are implemented rather than merely using other peoples implementations (and consequently a preference for open source software.

020111

Algorithm analysis. Application and implementation of some common data structures: stacks, queues, lists, priority queues, tables, sets and collections. Data representations including: arrays, linked lists, heaps, trees (including balanced trees) and hashing. Design of application programs making use of common data structures. Design and implementation of new data structures. Study of advanced algorithms in areas such as: graph theory, pattern searching and data compression. Access to the University's computer systems through an Internet service provider is compulsory for off-campus students

On-campus and Off-Campus Learning(OCL)

Examination (3 hours): 60%; In-semester assessment: 40%

FIT

GCO9808 or FIT1007 or FIT2034