Course Outline

CSC201 Data Structures and Algorithms

Course Coordinator:Mingzhong Wang (mwang@usc.edu.au) School:School of Science, Technology and Engineering

2026Trimester 2

UniSC Moreton Bay

UniSC Adelaide

Blended learning Most of your course is on campus but you may be able to do some components of this course online.

Please go to unisc.edu.au for up to date information on the
teaching sessions and campuses where this course is usually offered.

What is this course about?

Description

In the mobile world, devices need to meet hardware requirements for battery life and physical size. As such the efficiency of data representation and algorithm design are of critical importance. In this course, you will learn techniques for designing efficient algorithms and data storage. You will analyse time-and space-complexity of algorithms, identifying worst-case, average-case and best-case complexity. You will also use data structures including lists, stacks, queues, priority queues, search trees, hash tables, and graphs as well as algorithms for recursion, sorting and searching.

How will this course be delivered?

Activity Hours Beginning Week Frequency
Blended learning
Learning materials – Pre-recorded concept videos and associated activity 2hrs Week 1 12 times
Tutorial/Workshop 1 – On-Campus Computer Workshop 2hrs Week 1 12 times

Course Topics

  • Complexity analysis
  • Lists, stacks, queues, and hash tables
  • Trees and graphs
  • Recursion
  • Sorting and searching

What level is this course?

200 Level (Developing)

Building on and expanding the scope of introductory knowledge and skills, developing breadth or depth and applying knowledge and skills in a new context. May require pre-requisites where discipline specific introductory knowledge or skills is necessary. Normally, undertaken in the second or third full-time year of an undergraduate programs.

What is the unit value of this course?

12 units

How does this course contribute to my learning?

Course Learning Outcomes On successful completion of this course, you should be able to... Graduate Qualities Completing these tasks successfully will contribute to you becoming...
1 Demonstrate knowledge of data structure and algorithm fundamentals. Knowledgeable
2 Develop and evaluate solutions and systems for computing problems with time and/or space constraints. Empowered
3 Select, adapt, and design evidence-based/optimal solutions to complex computing problems. Creative and critical thinker
4 Describe and evaluate the impact of data structures and algorithms on resource utilisation. Sustainability-focussed
5 Communicate data structure and algorithmic analysis applied to a specific situation in reports, design documentation and specifications. Engaged

Am I eligible to enrol in this course?

Refer to the UniSC Glossary of terms for definitions of “pre-requisites, co-requisites and anti-requisites”.

Pre-requisites

ICT221

Co-requisites

Not applicable

Anti-requisites

Not applicable

Specific assumed prior knowledge and skills (where applicable)

Not applicable

Microcredential Information

Not applicable

How am I going to be assessed?

Grading Scale

Standard Grading (GRD)

High Distinction (HD), Distinction (DN), Credit (CR), Pass (PS), Fail (FL).

Details of early feedback on progress

Students will receive ongoing formative feedback during computer workshop and lecture sessions.

Assessment tasks

Delivery mode Task No. Assessment Product Individual or Group Weighting % What is the duration / length? When should I submit? Where should I submit it?
All 1 Artefact - Technical and Scientific, and Written Piece Individual 20%
Code and report
Week 5 Online Submission
All 2 Artefact - Technical and Scientific, and Written Piece Individual 40%
Code plus 1500 words
Week 11 Online Assignment Submission with plagiarism check
All 3 Examination - Centrally Scheduled Individual 40%
2 hours
Exam Period Online Assignment Submission with plagiarism check
All - Assessment Task 1:Storing and Using Data
Goal:
Understand, analyse, and improve the efficiency of software applications.
Product: Artefact - Technical and Scientific, and Written Piece
Authorship Statement:
Format:
1 software code package consisting of two solutions to a given problem utilising different data structures and algorithms, and 1 brief report identifying the algorithmic complexity of each solution.
Criteria:
No. Learning Outcome assessed
1
Demonstrated knowledge of data structure and algorithm fundamentals
1
2
Development and evaluation of software with respect to time and space constraints
2
3
Selection, adaption and design of solutions using principles of data structures and algorithms
3
Generic Skills:
Problem solving
All - Assessment Task 2:Coding project
Goal:
You will explore a case study with high time and/or space constraints in its runtime. You will use your knowledge of data structures and algorithms to design, justify and develop an application to meet the case study requirements.
Product: Artefact - Technical and Scientific, and Written Piece
Authorship Statement:
Format:
1 software application (code) satisfying the requirements of the case study and 1 report with 1500 words on design decisions justifying the chosen data structures and algorithms.
Criteria:
No. Learning Outcome assessed
1
Demonstrated knowledge of data structure and algorithm fundamentals
1
2
Development and evaluation of software with respect to time and space constraints
2
3
Selection, adaption and design of solutions using principles of data structures and algorithms
3
4
Explanation of the software design, the selection of data structures and algorithms, and implementation.
3 5
5
Description and evaluation of the case study according to sustainability and efficiency principles
4
Generic Skills:
Communication, Problem solving
All - Assessment Task 3:Final Exam
Goal:
The final exam will develop your ability to independently apply your skills and knowledge to solve familiar problem-based questions with confidence within a set time limit.
Product: Examination - Centrally Scheduled
Authorship Statement:
Format:
This examination consists of a set of questions on the use of data structures and algorithms. The questions are based on tutorial activities and lecture materials.
Criteria:
No. Learning Outcome assessed
1
Demonstrated knowledge of data structure and algorithm fundamentals
1
2
Development and evaluation of software with respect to time and space
2
3
Selection, adaption and design of solutions using principles of data structures and algorithms
3
Generic Skills:
Problem solving, Applying technologies

Directed study hours

A 12-unit course will have total of 150 learning hours which will include directed study hours (including online if required), self-directed learning and completion of assessable tasks. Student workload is calculated at 12.5 learning hours per one unit.

What resources do I need to undertake this course?

Please note: Course information, including specific information of recommended readings, learning activities, resources, weekly readings, etc. are available on the course Canvas site– Please log in as soon as possible.

Prescribed text(s) or course reader

You need regular access to the resource(s) below. Many texts are available as ebooks through the Library at no additional cost.

Required? Author Year Title Edition Publisher
Required Michael T. Goodrich,Roberto Tamassia,Michael H. Goldwasser 2014 Data Structures and Algorithms in Java 6th Edition John Wiley & Sons

Specific requirements

Not applicable

How are risks managed in this course?

Health and safety risks for this course have been assessed as low. It is your responsibility to review course material, search online, discuss with lecturers and peers and understand the health and safety risks associated with your specific course of study and to familiarise yourself with the University’s general health and safety principles by reviewing the online induction training for students, and following the instructions of the University staff.

What administrative information is relevant to this course?

Assessment: Academic Integrity

Academic integrity is the ethical standard of university participation. It ensures that students graduate as a result of proving they are competent in their discipline. This is integral in maintaining the value of academic qualifications. Each industry has expectations and standards of the skills and knowledge within that discipline and these are reflected in assessment.

Academic integrity means that you do not engage in any activity that is considered to be academic fraud; including plagiarism, collusion or outsourcing any part of any assessment item to any other person. You are expected to be honest and ethical by completing all work yourself and indicating in your work which ideas and information were developed by you and which were taken from others. You cannot provide your assessment work to others. You are also expected to provide evidence of wide and critical reading, usually by using appropriate academic references.

In order to minimise incidents of academic fraud, this course may require that some of its assessment tasks, when submitted to Canvas, are electronically checked through Turnitin. This software allows for text comparisons to be made between your submitted assessment item and all other work to which Turnitin has access.

Assessment: Additional Requirements

Eligibility for Supplementary Assessment

Your eligibility for supplementary assessment in a course is dependent of the following conditions applying:
(a) The final mark is in the percentage range 47% to 49.4%; and
(b) The course is graded using the Standard Grading scale

Assessment: Submission penalties

Late submissions may be penalised up to and including the following maximum percentage of the assessment task’s identified value, with weekdays and weekends included in the calculation of days late:
(a) One day: deduct 5%;
(b) Two days: deduct 10%;
(c) Three days: deduct 20%;
(d) Four days: deduct 40%;
(e) Five days: deduct 60%;
(f) Six days: deduct 80%;
(g) Seven days: A result of zero is awarded for the assessment task.

The following penalties will apply for a late submission for an online examination:
Less than 15 minutes: No penalty
From 15 minutes to 30 minutes: 20% penalty
More than 30 minutes: 100% penalty

Links to relevant University policy and procedures

For more information on Academic Learning & Teaching categories including:

  • Assessment: Courses and Coursework Programs
  • Review of Assessment and Final Grades
  • Supplementary Assessment
  • Central Examinations
  • Deferred Examinations
  • Student Conduct
  • Students with a Disability

For more information, visit https://www.usc.edu.au/explore/policies-and-procedures#academic-learning-and-teaching

Student Charter

UniSC is committed to excellence in teaching, research and engagement in an environment that is inclusive, inspiring, safe and respectful. The Student Charter sets out what students can expect from the University, and what in turn is expected of students, to achieve these outcomes.

General Enquiries

For course-specific questions, contact your teaching staff or Course Coordinator.  

For other enquiries or to access support, please contact Student Central: