Units / FIT3155
FIT3155 · Advanced data structures and algorithms
2026 Handbook6 credit pointsLevel 3Faculty of Information Technology
Last checked: 22 Aug 2026 UTCOverview
This unit builds on the concepts learnt in introductory algorithms and data structures study. It covers advanced algorithmic paradigms and problem-solving techniques required to address real-world programming challenges. It explores, in depth, the design and analysis of space-efficient data structures and time-efficient problem solving strategies to be used with them. Topics include amortized analysis, advanced sorting and searching algorithms, new tree/string/graph data structures and algorithms, and number-theoretic algorithms amongst others.
Areas of study: Advanced computer science Computational science
Offerings
| Campus | Teaching period | Mode |
|---|---|---|
| Clayton | First semester | Some activities have a choice of on-campus or online teaching activities (FLEXIBLE) |
| Malaysia | First semester | Teaching activities are on-campus (ON-CAMPUS) |
| Clayton | Second semester | Some activities have a choice of on-campus or online teaching activities (FLEXIBLE) |
| Malaysia | Second semester | Teaching activities are on-campus (ON-CAMPUS) |
Assessment
The Handbook lists an examination for this unit.
| # | Assessment | Type | Weight | Hurdle |
|---|---|---|---|---|
| 1 | Assignment 1 | Artefact | 20% | Threshold |
| 2 | Assignment 2 | Artefact | 20% | Threshold |
| 3 | Scheduled final assessment (2 hours and 10 minutes) | Examination | 60% | Threshold |
This unit has threshold mark hurdles. You must achieve at least 45% of the available marks in the final scheduled assessment, at least 45% in total for in-semester assessments, and an overall unit mark of 50% or more to be able to pass the unit. If you do not achieve the threshold mark, you will receive a fail grade (NH) and a maximum mark of 45 for the unit.
Assessment details may change. Please refer to the assessment information in Moodle closer to the start of the teaching period.
Requisites
prerequisite
- FIT2004 — Algorithms and data structures
Learning outcomes
- Analyse efficient data structures and effective algorithmic paradigms;
- Design and implement efficient algorithms and data structures for use on large data sets;
- Apply advanced algorithms and data structures to tackle complex computational problems;
- Prove the correctness of programs and reason about their space and time complexities.
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. Offers 2 x 1 hrs blocks of online workshop weekly (starting week 2).
| Activity | Duration |
|---|---|
| Laboratories | 33 hours |
| Seminars | 24 hours |
| Workshops | 22 hours |
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