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SIT221 - Data Structures and Algorithms


2020 unit information

Important Update:

Classes and seminars in Trimester 2/Semester 2, 2020 will be online. Physical distancing for coronavirus (COVID-19) will affect delivery of other learning experiences in this unit. Please check your unit sites for announcements and updates one week prior to the start of your trimester or semester.

Last updated: 2 June 2020

Offering information:

From 2021 - unit will be offered in Trimester 1 

Enrolment modes:Trimester 2: Burwood (Melbourne), Waurn Ponds (Geelong), Cloud (online)
Credit point(s):1
EFTSL value:0.125
Unit Chair:Trimester 2: Richard Dazeley

SIT131 or SIT232



Incompatible with:


Typical study commitment:

Students will on average spend 150 hours over the teaching period undertaking the teaching, learning and assessment activities for this unit.

Scheduled learning activities - campus:

2 x 1 hour classes per week, 1 x 2 hour practical per week.

Scheduled learning activities - cloud:

1 x 1 hour scheduled online workshop per week.


SIT221 introduces students to in memory data modelling and computational trade-offs when developing software. Computing platforms from Internet-Of-Things (IoT) devices to supercomputers have limited or restricted resources available to software engineers in terms of memory, computational power, and energy consumption. Writing efficient and high-quality programs is the technical skill every technology company is after. This unit will extend student programming capabilities by exploring the application and implementation of different data structures and algorithms and considerations associated with appropriate selection of these tools to meet different system requirements.


These are the Learning Outcomes (ULO) for this Unit

At the completion of this Unit
successful students can:

Deakin Graduate Learning Outcomes


Evaluate the memory usage and computational complexity of different solution strategies and use this to provide recommendations in terms of solution direction for given problem scenarios

GLO1: Discipline-specific knowledge and capabilities
GLO4: Critical thinking
GLO5: Problem solving


Create and use a range of data structures and algorithms to design solutions and implement programs that address specified requirements and constraints

GLO1: Discipline-specific knowledge and capabilities
GLO5: Problem solving


Document problem and solution constraints, design decisions, and trade-offs involved in creating software solutions for a given problem

GLO2: Communication

These Unit Learning Outcomes are applicable for all teaching periods throughout the year


Assessment Description Student output Weighting (% total mark for unit) Indicative due week
Learning portfolio portfolio 100% Week 12

The assessment due weeks provided may change. The Unit Chair will clarify the exact assessment requirements, including the due date, at the start of the teaching period.

Hurdle requirement

To be eligible to obtain a pass in this unit, students must meet certain milestones as part of the portfolio.

Learning Resource

There is no prescribed text. Unit materials are provided via the unit site. This includes unit topic readings and references to further information.

Unit Fee Information

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