Data Structures and Patterns

COS30008 12.5 Credit Points Hawthorn, Sarawak Available to incoming Study Abroad and Exchange students


  • One Semester or equivalent

Contact hours

  • 48 Hours

On-campus unit delivery combines face-to-face and digital learning.

2022 teaching periods


Higher Ed. Semester 1

28 Feb 22 - 29 May 22

5 Jul 22

Last self enrolment:
13 Mar 22

31 Mar 22

Last withdraw without fail:
15 Apr 22

Aims and objectives

This unit of study aims to study the design, implementation, and application of data structures as a means for algorithmic problem solving. Each problem exhibits specific characteristics with respect to resource requirements, data representation, and software architecture. The study of data structures is primarily concerned with the following questions: How can a given problem be effectively expressed? What are suitable data representations for specifying computational processes? What is the impact of data and its representation with respect to time and space consumption? What are the reoccurring structural artefacts in software and how can we identify them in order to facilitate problem solving?
Unit Learning Outcomes
On successful completion of this unit students will be able to:
#Unit Learning Outcome Description
ULO1Apply object oriented design and implementation techniques (K1, K3, K4, K6, S1, S2, S3)
ULO2Interpret the trade-offs and issues involved in the design, implementation, and application of various data structures with respect to a given problem (K1, K2, K4, K6, S1, S2, S3)
ULO3Design, implement, and evaluate software solutions using behavioural, creational, and structures software design patterns (K3, K4, K6, S1, S2, S3)
ULO4Explain the purpose and answer questions about data structures and design patterns that illustrate strengths and weaknesses with respect to resource consumption (K1, K3, K6, S1, S2, S3, A2)
ULO5Assess the impact of data structures on algorithms (K1, K2, K3, K4, K6, S1, S2, S3)
ULO6Analyse algorithm designs and perform best-, average-, and worst-case analysis (K1, K2, K3, K4, K6, S1, S2)