Course coordinator
Dr Thilina Halloluwa
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
Working on large and complex software systems and ensuring those systems remain maintainable requires disciplined, individual practices. Software must be well-specified, well-implemented and well-tested. This course covers concepts and techniques in modern programming languages that help support good practice (such as OO concepts, genericity and exception handling) with specific application to file IO and GUIs in Java.
To effectively manage the complexity of large software systems, higher-level language constructs are required. In particular, classes to implement independent abstractions with robust and compact interfaces are required. This course utilizes the Java programming language to introduce students to the details of concepts such as object-oriented programming, data abstraction, design, refactoring and unit testing. These concepts are used to refine the quality of ones individual code contributions such that the contribution is suitable to be integrated with large software systems.
Course requirements
Assumed background
You are expected to have successfully completed at least one programming course in a high-level object-oriented programming language (e.g. Python, C#, JavaScript, etc.) and be familiar with programming constructs such as variables, control structures, functions/methods, objects, classes, and inheritance.
Prerequisites
You'll need to complete the following courses before enrolling in this one:
CSSE1001 or ENGG1001
Incompatible
You can't enrol in this course if you've already completed the following:
COMP2500 or COMP7908 or CSSE7023
Course contact
Course staff
Lecturer
Dr Thilina Halloluwa
Timetable
The timetable for this course is available on the UQ Public Timetable.
Additional timetable information
You must sign up for one practical and one contact session.
Lectures begin in week 1. Contact and practical classes begin in week 2.
Aims and outcomes
Working on large and complex software systems and ensuring those systems remain maintainable requires disciplined, individual practices. Software must be well-specified, well-implemented and well-tested. This course covers concepts and techniques in modern programming languages that help support good practice (such as data abstraction, genericity and exception handling).
Learning outcomes
After successfully completing this course you should be able to:
LO1.
Implement object-oriented programs according to their specifications.
LO2.
Test components of object-oriented programs (using a testing framework).
LO3.
Write, document and analyse code which uses language features such as inheritance, interfaces, exceptions and I/O.
LO4.
Judge whether a program follows good practice.
LO5.
Write, interpret and critique specifications for program modules (e.g. classes or interfaces).
Assessment
Assessment summary
| Category | Assessment task | Weight | Due date |
|---|---|---|---|
| Tutorial/ Problem Set | On-line problems (ShiFoo) | 10% |
Week 2 Tue - Week 13 Tue
The due day and time for submissions will be 1pm Tuesday, unless otherwise indicated. |
| Computer Code | Assignment 1 | 20% |
27/08/2024 1:00 pm |
| Computer Code | Assignment 2 | 25% |
15/10/2024 1:00 pm |
| Examination |
Final Exam
|
45% |
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
On-line problems (ShiFoo)
- Mode
- Written
- Category
- Tutorial/ Problem Set
- Weight
- 10%
- Due date
Week 2 Tue - Week 13 Tue
The due day and time for submissions will be 1pm Tuesday, unless otherwise indicated.
- Learning outcomes
- L01, L02, L03, L04
Task description
You will be given sets of programming problems to solve during the semester. These problem sets will be delivered and submitted via the ShiFoo online environment. In addition to implementing solutions to the problems, the problems may include components of reviewing code quality. Refer to the assessment description on Blackboard.
A link to this environment is available on Blackboard. Each set of problems will reinforce concepts delivered in the course.
A schedule of activities and due dates will be published on Blackboard. The due day and time for submissions will be Tuesday at 1pm, unless otherwise indicated.
You may also be asked to attend an interview about your submission (see the Additional assessment information section below).
Submission guidelines
Deferral or extension
You cannot defer or apply for an extension for this assessment.
No extensions available and 100% late penalty applied for the weekly online quizzes. To accommodate unforeseen circumstances such as illness, your quiz score will be based on the best 10 out of 12 submissions.
Assignment 1
- Mode
- Product/ Artefact/ Multimedia, Written
- Category
- Computer Code
- Weight
- 20%
- Due date
27/08/2024 1:00 pm
- Learning outcomes
- L01, L02, L03, L05
Task description
This assignment will provide practice at implementing Java programs to a given specification. The assignment will also require students to critically look at a given problem and write comprehensive automated tests for your Java program.
You may also be asked to attend an interview about your submission (see the Additional assessment information section below).
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
Submission guidelines
Online via Gradescope unless otherwise specified for a particular assessment item.
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 submissions 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
Assignment submissions received after the due time (or any approved extended deadline) will be subject to a 100% late penalty. A one-hour grace period applies to the due time after which time the 100% late penalty will be imposed. This grace period is designed to deal with issues that might arise during submission (e.g. delays with Blackboard or Gradescope) and should not be considered a shift of the due time.
Assignment 2
- Mode
- Product/ Artefact/ Multimedia, Written
- Category
- Computer Code
- Weight
- 25%
- Due date
15/10/2024 1:00 pm
- Learning outcomes
- L01, L02, L03, L04, L05
Task description
This assignment will provide practice at implementing/reviewing software in Java, as well as, debugging software based on automated test feedback and refactoring software to be more maintainable, readable, and re-usable. Additionally, you may be required to write a report on design/implementation decisions you made to improve the software.
You may also be asked to attend an interview about your submission (see the Additional assessment information section below).
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
Submission guidelines
Online via Gradescope unless otherwise specified for a particular assessment item.
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.
Late submission
Assignment submissions received after the due time (or any approved extended deadline) will be subject to a 100% late penalty. A one-hour grace period applies to the due time after which time the 100% late penalty will be imposed. This grace period is designed to deal with issues that might arise during submission (e.g. delays with Blackboard or Gradescope) and should not be considered a shift of the due time.
Final Exam
- Hurdle
- Identity Verified
- In-person
- Mode
- Written
- Category
- Examination
- Weight
- 45%
- Due date
End of Semester Exam Period
2/11/2024 - 16/11/2024
- Learning outcomes
- L01, L02, L03, L04, L05
Task description
The final exam will be an on-campus, invigilated paper-based exam.
The exam has specified materials permitted. One A4 sheet of handwritten or typed notes double-sided is permitted. You may use a Casio fx-82 or UQ approved and labelled calculator. Rough paper will be provided.
The exam covers all course materials from the whole semester. Question formats may include multiple choice, short answer and calculations, and programming tasks.
Hurdle requirements
At least 40% is required on the final examination to get above a final grade of 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, double 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 % | Description |
|---|---|---|
| 1 (Low Fail) | 0 - 19 |
Absence of evidence of achievement of course learning outcomes. Course grade description: Overall mark is in the range 0 to 19. |
| 2 (Fail) | 20 - 44 |
Minimal evidence of achievement of course learning outcomes. Course grade description: Overall mark is in the range 20 to 44. |
| 3 (Marginal Fail) | 45 - 49 |
Demonstrated evidence of developing achievement of course learning outcomes Course grade description: Overall mark is in the range 45 to 49 OR overall mark is > 49 but the final exam mark is < 40%. |
| 4 (Pass) | 50 - 64 |
Demonstrated evidence of functional achievement of course learning outcomes. Course grade description: Overall mark is in the range 50 to 64 AND the final exam mark is >= 40%. |
| 5 (Credit) | 65 - 74 |
Demonstrated evidence of proficient achievement of course learning outcomes. Course grade description: Overall mark is in the range of 65 to 74 AND the final exam mark is >= 40%. |
| 6 (Distinction) | 75 - 84 |
Demonstrated evidence of advanced achievement of course learning outcomes. Course grade description: Overall mark is in the range of 75 to 84 AND the final exam mark is >= 40%. |
| 7 (High Distinction) | 85 - 100 |
Demonstrated evidence of exceptional achievement of course learning outcomes. Course grade description: Overall mark is in the range of 85 to 100 AND the final exam mark is >= 40%. |
Additional course grading information
Your overall mark will be the weighted sum of the marks for all assessment components, based on the weighting in the table above.
Your overall mark (only) will be rounded to the nearest whole number before any grade cutoffs apply.
If you achieve less than 40% of the available marks in the final exam, your grade will be capped at a 3.
In other words, where A1, A2, S, and E represent your mark as a percentage (between 0-100 inclusive) on Assignment 1, Assignment 2, ShiFoo, and the Final Exam respectively, your overall mark out of 100, M, will be:
M = ROUND(0.2 × A1 + 0.25 × A2 + 0.1 × S + 0.45 × E)
The course coordinator reserves the right to moderate marks.
Supplementary assessment
Supplementary assessment is available for this course.
Additional assessment information
Plagiarism and Generative AI
All assignments are to be worked on individually and must be your own work except where the use of code written or provided by other entities (teaching staff, AI tools, etc.) is explicitly permitted by the assignment specification, and any such code is referenced in the manner required in the assignment specification.
All submitted code will be subject to electronic plagiarism and collusion detection. Assignments with no academic merit will be awarded a mark of zero. You may have to verbally answer questions about your submission as part of the assignment marking process.
Assessment Interviews
For the programming assignments and Shifoo exercises, the teaching staff may conduct interviews with a subset of students about their submissions to establish genuine authorship.
- If you write your own code, you have nothing to fear from this process. If you legitimately use permitted code from other sources (following the usage/referencing requirements in the assignment specification) then you are expected to understand that code.
- If you are not able to adequately explain the design of your solution and/or adequately explain your submitted code and/or be able to make simple modifications to your solution as requested at the interview, then your assignment mark will be scaled down based on the level of understanding you are able to demonstrate and/or your submission may be subject to a misconduct investigation where your interview responses form part of the evidence.
Interview invitations will be issued by email to your student email account at any time up until the end of week one of the exam period. Failure to respond to an interview invitation by the deadline stated in the invitation (which will be at least one week after the invitation is sent) or failure to attend a scheduled interview may result in zero marks for the assignment unless exceptional circumstances can be demonstrated with supporting evidence.
Grade Integrity
If there are administrative errors (e.g., marks added up incorrectly) in your grade or feedback - speak to a member the course teaching staff. and we will fix it. For all other remarking requests refer to Querying a result on my.UQ: https://my.uq.edu.au/querying-result
Support
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
Blackboard The course Blackboard site (learn.uq.edu.au) will be the entry point for access to all course resources. Important announcements will be made on this blackboard. Check the announcements regularly; at least once a week and more often in the week before assignments are due.
Ed Discussion The course will use the Ed Discussion as a Q&A forum. Students are encouraged to ask questions on this discussion board and answer questions of their peers. Do not publicly post assessed items on the forum as this may result in Academic Misconduct. If you are unsure, ask before posting.
Gradescope Assignments will be submitted via the Gradescope platform. You can access this via a link in Blackboard throughout the semester as it is released for each assignment. Ensure that you upload your submissions early and regularly and check that what you submitted to Gradescope is what you intended, and not, for example, an out of date submission. Some feedback will be available immediately after submission, ensure there are no failures that prevent your submission from being tested.
ShiFoo The course uses the ShiFoo online environment for weekly programming assessment. This is available via a link in Blackboard.
Development Environment Students will be required to write programs in Java. The course will use the latest Long-Term Support (LTS) version of Java, which is Java 21. You should install an Integrated Development Environment (IDE), such as JetBrains IntelliJ (recommended). An IDE provides access to a sophisticated development environment, as well as the standard compilation tools.
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 |
Lecture |
Lectures Learning outcomes: L01, L02, L03, L04, L05 |
General contact hours |
Contacts There will be weekly tutorials starting in week 2. Learning outcomes: L02, L03, L04, L05 |
|
Practical |
Practicals There will be weekly prac sessions starting in week 2. Learning outcomes: L01, L02, L03, L05 |
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: