FIT2004 · Algorithms and data structures

Overview

This unit introduces you 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.

Areas of study: Computer science Computational science

Offerings

Assessment

The Handbook does not list a final examination among the assessment items. That is not a guarantee there is none.

Assessment details may change. Please refer to the assessment information in Moodle closer to the start of the teaching period.

Requisites

Learning outcomes

1. Analyse general problem solving strategies and algorithmic paradigms, and apply them to solving new problems;
2. Prove correctness of programs, analyse their space and time complexities;
3. Compare and contrast various abstract data types and use them appropriately;
4. Develop and implement algorithms to solve computational problems.

Workload

Minimum total expected workload to achieve the learning outcomes for this unit is 144 hours per semester typically comprising a mixture of scheduled online and face to face learning activities and independent study. Independent study may include associated reading and preparation for scheduled teaching activities. Applied sessions are scheduled from Week 2 to Week 12.

Student experience, not official rules. Nothing here changes what the Handbook says.