Course coordinator
Dr Joel Mackenzie
Course overview
- Study period
- Semester 2, 2024 (22/07/2024 - 18/11/2024)
- Study level
- Undergraduate
- Location
- St Lucia
- Attendance mode
- In Person
- Units
- 2
- Administrative campus
- St Lucia
- Coordinating unit
- Elec Engineering & Comp Science School
Data structures and types, mapping of abstract information structures into representations on primary and secondary storage. Analysis of time and space complexity of algorithms. Sequences. Lists. Stacks. Queues. Sets, multisets, tables. Trees. Sorting. Hash tables. Priority queues. Graphs. String algorithms.
This course will introduce data structures and algorithms that are important for designing computer programs with performance guarantees and constitute the basis of complex software systems. Broadly speaking, this course will teach you to think - and to solve problems - like a computer scientist. The course will also cover a set of analytical techniques that are fundamental for advanced studies in theoretical computer science. Changes to this offering include moving from Gradescope quizzes to RiPPLE tasks to improve student engagement, and minor improvements to course material including lecture slides and tutorial questions.
Course requirements
Assumed background
Prior programming experience in an object-oriented language (e.g. Python, Java, C++, C#, etc.),ﾠwith a good understanding of the principle of encapsulation,ﾠis assumed.
Prerequisites
You'll need to complete the following courses before enrolling in this one:
CSSE2002 and (MATH1061 or (CSSE2010 and STAT2202))
Incompatible
You can't enrol in this course if you've already completed the following:
COMP2502 or COMP7505
Jointly taught details
This course is jointly-taught with:
- COMP7505
All learning activities are jointly taught.
Course contact
Course staff
Lecturer
Dr Joel Mackenzie
Timetable
The timetable for this course is available on the UQ Public Timetable.
Aims and outcomes
This course will build an understanding of how the architecture of a computer impacts the construction of programs and how data structures and algorithms can be constructed to efficiently perform desired functionality. The goal of this course is to build enough understanding of data structures and associated algorithms so that an appropriate set can be selected in the design of new software. The students should develop an understanding of:
- How computer data structures impact the performance of complex software;
- Fundamental algorithms and data structuresﾠincluding their time and space requirements;
- How to select appropriate data structures and algorithms to settle practical problems;
- Mathematical techniques for designing and analysing algorithms with performance guarantees.
Learning outcomes
After successfully completing this course you should be able to:
LO1.
Understand the principles of data structures - Understand the internal workings of fundamental data structures and algorithms
LO2.
Understand the principles of data structures - Determine the running time and memory space usage of common algorithms.
LO3.
Develop algorithmic solutions - Analyse the performance of fundamental data structures and algorithms
LO4.
Develop algorithmic solutions - Adapt or invent new algorithms and data structures for software engineering problems.
LO5.
Develop algorithmic solutions - Select and justify appropriate combinations of data structures and algorithms to solve software engineering problems.
LO6.
Develop algorithmic solutions - Communicate the efficiency and correctness of identified solutions
Assessment
Assessment summary
| Category | Assessment task | Weight | Due date |
|---|---|---|---|
| Participation/ Student contribution, Quiz, Tutorial/ Problem Set |
RiPPLE Activities
|
10% (Best 7 of 9) |
5/08/2024 4:00 pm 12/08/2024 4:00 pm 26/08/2024 4:00 pm 2/09/2024 4:00 pm 9/09/2024 4:00 pm 16/09/2024 4:00 pm 30/09/2024 4:00 pm 8/10/2024 4:00 pm 21/10/2024 4:00 pm
Note that the Week 11 task is due on Tuesday (of Week 11) due to the Monday being a public holiday. |
| Computer Code |
Assignment 1
|
15% |
23/08/2024 3:00 pm |
| Computer Code |
Assignment 2
|
25% |
18/10/2024 3:00 pm |
| Examination |
Final Exam
|
50% |
End of Semester Exam Period 2/11/2024 - 16/11/2024 |
A hurdle is an assessment requirement that must be satisfied in order to receive a specific grade for the course. Check the assessment details for more information about hurdle requirements.
Assessment details
RiPPLE Activities
- Online
- Mode
- Written
- Category
- Participation/ Student contribution, Quiz, Tutorial/ Problem Set
- Weight
- 10% (Best 7 of 9)
- Due date
5/08/2024 4:00 pm
12/08/2024 4:00 pm
26/08/2024 4:00 pm
2/09/2024 4:00 pm
9/09/2024 4:00 pm
16/09/2024 4:00 pm
30/09/2024 4:00 pm
8/10/2024 4:00 pm
21/10/2024 4:00 pm
Note that the Week 11 task is due on Tuesday (of Week 11) due to the Monday being a public holiday.
Task description
RiPPLE activities are designed to demonstrate your ability to understand data structures, solve simple algorithmic problems, compute the time and space complexity of algorithms, and optimize their computational complexity. These activities are designed to keep students engaged with the week-by-week teaching material.
The assessable tasks will consist of a combination of learning resource creation, moderation and practice. Submissions will be due at the start of each teaching week beginning in Week 3 and ending in Week 13. The best 7 of 9 submissions will be used to calculate a student's mark, with each submission weighted equally. Detailed task specifications will be announced and placed on Blackboard at the start of the semester.
Submission guidelines
The assessment will be submitted online via the RiPPLE platform. Detailed instructions will be provided in the task specification.
Deferral or extension
You cannot defer or apply for an extension for this assessment.
No extensions available and 100% Late penalty applied for the online quizzes. To accommodate unforeseen circumstances such as illness, the best 7 of 9 submissions will contribute to the total RiPPLE mark, allowing for two missed submissions across the semester.
Assignment 1
- Mode
- Written
- Category
- Computer Code
- Weight
- 15%
- Due date
23/08/2024 3:00 pm
- Other conditions
- Student specific.
Task description
In the first assignment, you will demonstrate your ability to implement and use simple data structures and algorithms to solve a computing problem.
Submission guidelines
Via submission link on Gradescope.
Deferral or extension
You may be able to apply for an extension.
The maximum extension allowed is 7 days. Extensions are given in multiples of 24 hours.
Marked assignments with feedback and/or detailed solutions with feedback will be released to students within 7-14 days where the earlier time frame applies if no extensions.
Late submission
100% Late Penalty after 1 hour grace period. The one-hour grace period is recorded from the time the submission is due.
Assignment 2
- Mode
- Written
- Category
- Computer Code
- Weight
- 25%
- Due date
18/10/2024 3:00 pm
- Other conditions
- Student specific.
Task description
In the second assignment, you will demonstrate your ability to implement and use complex data structures and algorithms to solve an advanced computing problem. You will also be expected to provide analysis that communicates time and space complexity of a given algorithm.
Submission guidelines
Via submission link on Blackboard/Gradescope.
Deferral or extension
You may be able to apply for an extension.
The maximum extension allowed is 7 days. Extensions are given in multiples of 24 hours.
Marked assignments with feedback and/or detailed solutions with feedback will be released to students within 7-14 days where the earlier time frame applies if no extensions.
Late submission
100% Late Penalty after 1 hour grace period. The one-hour grace period is recorded from the time the submission is due.
Final Exam
- Hurdle
- Mode
- Written
- Category
- Examination
- Weight
- 50%
- Due date
End of Semester Exam Period
2/11/2024 - 16/11/2024
Task description
A two-hour invigilated final examination will be held during the final examination period. It aims to test the students' understanding of topics covered by the whole course. The exam will be closed-book. The examination is centrally timetabled.
Hurdle requirements
Students must achieve at least 50% on the final exam in order to pass this course. If you achieve less than 50% in the final examination, your overall final marks will be capped at 49, and your final grade will be capped at 3.Exam details
| Planning time | 10 minutes |
|---|---|
| Duration | 120 minutes |
| Calculator options | (In person) Casio FX82 series only or UQ approved and labelled calculator |
| Open/closed book | Closed Book examination - specified written materials permitted |
| Materials | One A4 sheet of handwritten or typed notes, single sided, is permitted |
| Exam platform | Paper based |
| Invigilation | Invigilated in person |
Submission guidelines
Deferral or extension
You may be able to defer this exam.
Course grading
Full criteria for each grade is available in the Assessment Procedure.
| Grade | Cut off Percent | Description |
|---|---|---|
| 1 (Low Fail) | 0 - 19 |
Absence of evidence of achievement of course learning outcomes. |
| 2 (Fail) | 20 - 44 |
Minimal evidence of achievement of course learning outcomes. |
| 3 (Marginal Fail) | 45 - 49 |
Demonstrated evidence of developing achievement of course learning outcomes |
| 4 (Pass) | 50 - 64 |
Demonstrated evidence of functional achievement of course learning outcomes. |
| 5 (Credit) | 65 - 74 |
Demonstrated evidence of proficient achievement of course learning outcomes. |
| 6 (Distinction) | 75 - 84 |
Demonstrated evidence of advanced achievement of course learning outcomes. |
| 7 (High Distinction) | 85 - 100 |
Demonstrated evidence of exceptional achievement of course learning outcomes. |
Additional course grading information
Students must achieve at least 50% on the final exam in order to pass this course. If you achieve less than 50% in the final examination, your overall final marks will be capped at 49, and your final grade will be capped at 3.
Supplementary assessment
Supplementary assessment is available for this course.
Additional assessment information
Mark Rounding:ﾠ Course marks will be rounded to the nearest grade before application of grade cut-offs (eg: 74.4 becomes 74; 74.5 becomes 75).
Moderation: The course coordinator reserves the right to moderate marks.
Generative AI Policy
- Assignments: Artificial Intelligence (AI) and Machine Translation (MT) are emerging tools that may support students in completing this assessment task. Students may appropriately use AI and/or MT in completing this assessment task. Students must clearly reference any use of AI or MT in each instance. A failure to reference generative AI or MT use may constitute student misconduct under the Student Code of Conduct.
- RiPPLE: This assessment task evaluates students' abilities, skills and knowledge without the aid of generative Artificial Intelligence (AI) or Machine Translation (MT). Students are advised that the use of AI technologies to develop responses is strictly prohibited and may constitute student misconduct under the Student Code of Conduct.
Having Troubles? If you are having difficulties with any aspect of the course material you should seek help. Speak to the course teaching staff.
If external circumstances are affecting your ability to work on the course, you should seek help as soon as possible. The University and UQ Union have organisations and staff who are able to help, for example, UQ Student Services are able to help with study and exam skills, tertiary learning skills, writing skills, financial assistance, personal issues, and disability services (among other things).
Complaints and criticisms should be directed in the first instance to the course coordinator. If you are not satisfied with the outcome, you may bring the matter to the attention of the School of EECS Director of Teaching and Learning.
Learning resources
You'll need the following resources to successfully complete the course. We've indicated below if you need a personal copy of the reading materials or your own item.
Library resources
Find the required and recommended resources for this course on the UQ Library website.
Additional learning resources information
Facilities
There will be no special access to a computer lab for this course. ﾠPlease see the EECS Student Guide for information on expectations and requirements for the use of the computer labs.
Blackboard
Course material and announcements will appear on Blackboard at https://learn.uq.edu.au/. The Blackboard website should be checked for announcements regularly; at least once a week and more often in the week before assignments are due. Note that solutions or partial solutions to individual assignments should not be posted on any public forum. If you are uncertain about whether or not a post is appropriate, please contact the teaching staff for clarification. The blackboard will also contain links to other relevant tools such as the Ed discussion forum or Gradescope.
Sample exams
Some past exams are available from the library. See: http://www.library.uq.edu.au/exams/
Learning activities
The learning activities for this course are outlined below. Learn more about the learning outcomes that apply to this course.
Filter activity type by
Please select
| Learning period | Activity type | Topic |
|---|---|---|
Multiple weeks From Week 1 To Week 13 |
Lecture |
Lectures |
Multiple weeks From Week 2 To Week 13 |
Tutorial |
Contacts |
Policies and procedures
University policies and procedures apply to all aspects of student life. As a UQ student, you must comply with University-wide and program-specific requirements, including the:
- Student Code of Conduct Policy
- Student Integrity and Misconduct Policy and Procedure
- Assessment Procedure
- Examinations Procedure
- Reasonable Adjustments - Students Policy and Procedure
Learn more about UQ policies on my.UQ and the Policy and Procedure Library.
School guidelines
Your school has additional guidelines you'll need to follow for this course: