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Unit of study_
COMP9123: Data Structures and Algorithms
2025 unit information
This unit will teach some powerful ideas that are central to solving algorithmic problems in ways that are more efficient than naive approaches. In particular, students will learn how data collections can support efficient access, for example, how a dictionary or map can allow key-based lookup that does not slow down linearly as the collection grows in size. The data structures covered in this unit include lists, stacks, queues, priority queues, search trees, hash tables, and graphs. Students will also learn efficient techniques for classic tasks such as sorting a collection. The concept of asymptotic notation will be introduced, and used to describe the costs of various data access operations and algorithms.
Unit details and rules
Managing faculty or University school:
Engineering
| Study level | Postgraduate |
|---|---|
| Academic unit | Computer Science |
| Credit points | 6 |
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Prerequisites:
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None |
|---|---|
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Corequisites:
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None |
| Prohibitions:
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INFO1105 or INFO1905 or COMP2123 or COMP2823 |
| Assumed knowledge:
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Discrete mathematics and probability (e.g. MATH1064 or equivalent) and programming experience (e.g. INFO1110 or COMP9001 or equivalent) |
At the completion of this unit, you should be able to:
- LO1. demonstrate proficiency in organising, presenting and discussing professional ideas and issues in oral, written and graphic formats. Thorough descriptive reporting. With thorough consideration of format and audience requirements. Fluent presentation of engineering/IT concepts and issues to professional and non-professional audiences, using a varied range of professional communication tools and formats
- LO2. design an algorithmic solution to a problem, coding it, analysing its complexity, and evaluating its suitability to a context
- LO3. write code that recursively performs an operation on a data structure
- LO4. apply basic algorithmic techniques (e.g. divide-and-conquer, greedy) to given design tasks
- LO5. use notation of big-Oh to represent asymptotic growth of cost functions
- LO6. understand commonly used data structures, e.g., lists, stacks, queues, priority queues, search trees, hash tables, and graphs. This covers the way information is represented in each structure, algorithms for manipulating the structure, and analysis of asymptotic complexity of the operations
- LO7. understand basic algorithms related to data structures, such as algorithms for sorting, tree traversals, and graph traversals
- LO8. use mathematical methods to evaluate the performance of an algorithm.
Unit availability
This section lists the session, attendance modes and locations the unit is available in. There is a unit outline for each of the unit availabilities, which gives you information about the unit including assessment details and a schedule of weekly activities.
The outline is published 2 weeks before the first day of teaching. You can look at previous outlines for a guide to the details of a unit.
| Session | MoA ? | Location | Outline ? |
|---|---|---|---|
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Semester 1 2024
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Normal day | Camperdown/Darlington, Sydney | |
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Semester 2 2024
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Normal evening | Camperdown/Darlington, Sydney |
| Session | MoA ? | Location | Outline ? |
|---|---|---|---|
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Semester 1 2025
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Normal evening | Camperdown/Darlington, Sydney |
Outline unavailable
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Semester 2 2025
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Normal evening | Camperdown/Darlington, Sydney |
Outline unavailable
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Modes of attendance (MoA)
This refers to the Mode of attendance (MoA) for the unit as it appears when you’re selecting your units in Sydney Student. Find more information about modes of attendance on our website.
