Course Coordinator:Mingzhong Wang (mwang@usc.edu.au) School:School of Science, Technology and Engineering
UniSC Moreton Bay |
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 usc.edu.au for up to date information on the
teaching sessions and campuses where this course is usually offered.
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.
Activity | Hours | Beginning Week | Frequency |
Blended learning | |||
Learning materials – Pre-recorded concept videos and associated activity | 2hrs | Week 1 | 13 times |
Tutorial/Workshop 1 – On-Campus Computer Workshop | 2hrs | Week 1 | 13 times |
200 Level (Developing)
12 units
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 |
Refer to the UniSC Glossary of terms for definitions of “pre-requisites, co-requisites and anti-requisites”.
ICT221
Not applicable
Not applicable
Not applicable
Standard Grading (GRD)
High Distinction (HD), Distinction (DN), Credit (CR), Pass (PS), Fail (FL). |
Students will receive ongoing formative feedback during computer workshop and lecture sessions.
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 6 | Online Submission |
All | 2 | Artefact - Technical and Scientific, and Written Piece | Individual | 40% | Code plus 1500 words |
Week 13 | 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 |
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: |
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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 |
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: |
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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 |
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: |
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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.
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.
Please note that you need to have regular access to the resource(s) listed below. Resources may be required or recommended.
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 |
Not applicable
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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.
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