FIT5211 - Algorithms and data structures - 2017

This unit introduces students to problem solving concepts and techniques fundamental to the science of programming. It covers data types; data structures; algorithms; algorithmic complexity; and recursion. Detailed topics include analysis of best and worst-case time complexity; data structures such as lists, stacks, queues, binary search trees, graphs and heaps; hashing; sorting algorithms; searching algorithms; and graph algorithms. Students will implement these algorithms and data structures in the Python programming language.

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

1. design and implement simple algorithms in Python;
2. implement basic data types such as stacks, queues, lists, trees, priority queues, heaps and hash tables;
3. compare and evaluate different algorithms and implementations of basic data types;
4. calculate best case and worst case big-O algorithm complexity.

Semester 1: Examination (3 hours): 50%; In-semester assessment: 50%

Semester 2: Examination (2 hours): 50%; In-semester assessment: 50%

Minimum total expected workload equals 12 hours per week comprising:

1. Contact hours for on-campus students:
   • Two hour lectures
   • One hour tutorial
   • Two hour laboratory
2. Additional requirements (all students):
   • A minimum of 7 hours of personal study per week in order to satisfy the reading, lab and assignment expectations.

See also Unit timetable information

Professor Bernd Meyer

FIT9133

FIT9059