The original unit GCO2817 is being redefined

30 March 2017: Consulted with Reza Haffari (Chief Examiner) and Johan Vorster (MSA Lecturer), and on their behalf updating exam to 2 hours as required by new University Examination Procedures (confirmed to remain at 60%). Effective S2 2017.

02/12/2015: Update objectives to learning outcomes for AQF compliance. Effective immediately.

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

19/9/2019: Admin - updating exam duration to include additional 10 minutes as per University requirement.

4/5/2020: As the MSA course 4307 Bachelor of Computer and Information Sciences is in teach-out, the MSA offering of this unit has been re-coded to FZA2009 effective Semester 2, 2020. These units will be managed by South Africa and therefore no separate Monatar entries will be made

30/09/2020 Admin: Update to include new assessment and teaching approach fields as per Handbook requirements.

19/11/2020: Admin - this unit was disestablished at FEC 5/20 on 12/11/2020 as it is no longer required.

This unit is a requirement in the Applications Development and Networks major of the BITS. It provides students with knowledge and experience in: the application and implementation of some common data structures; data representations; the design of application programs; and the design and implementation of new data structures. It also provides opportunity for the study of advanced algorithms.

At the completion of this unit, students should be able to:

1. analyse simple algorithms to work out an order of magnitude estimate of running time and space;
2. describe and implement the most common data structures: stacks, queues, lists, priority queues, tables, sets, collections using various common data representations: arrays, linked lists, heaps, trees (including balanced trees), hashing;
3. evaluate which implementation would be most appropriate for a given data structure and application;
4. apply the same principles used in implementing the common data structures to implement other data structures and design and implement new data structures;
5. describe 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);
6. design new algorithms to solve new problems.

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)

Lecture and tutorials or problem classes:

Examination (2 hours and 10 minutes): 60%; In-semester assessment: 40%

1. Programming Assignments: 20% - ULO ?
2. Theory Assignments: 20% - ULO ?
3. Examination: 60% - ULO ?

Minimum total expected workload equals 12 hours per week comprising:

(a.) Contact hours for on-campus students:

(b.) Study schedule for off-campus students:

(c.) Additional requirements (all students):

FIT

FIT1007 or GCO1812 or GCO9808 or FIT2034

Sheelagh Walton