Introduction to Software Engineering (CSSE1001)

Course overview

Introduction to Software Engineering through programming with particular focus on the fundamentals of computing and programming, using an exploratory problem-based approach. Building abstractions with procedures, data and objects; data modelling; designing, coding and debugging programs of increasing complexity

This course introduces fundamental concepts in software engineering, using the Python programming language. Emphasis is placed on problem solving using computational techniques, creating algorithms and designing classes.

Due to student feedback the module on GUIs has been removed from this course in order to allocate more time to the remaining topics.

Course requirements

Assumed background

No prior knowledge ofﾠprogramming is assumed.

Incompatible

You can't enrol in this course if you've already completed the following:

COMP1502, CSSE7030, ENGG1001

Course contact

Course staff

Timetable

The timetable for this course is available on the UQ Public Timetable.

Additional timetable information

Students may attend additional contact sessions, beyond the one to which they are allocated, if there are not too many students in the room for the demonstrators to manage, they may limit attendance to only those allocated.

Practical sessions tend to become very crowded close to assignment due dates. Demonstrators may limit attendance to only those allocated to a practical session to ensure that the session is manageable.

Lectures will be recorded and available on the course Blackboard site. However, attendance at the physical lecture is strongly recommended, with recordings used to revise content.

Aims and outcomes

This course focuses on the organising ideas of software design and construction. Because software systems are highly complex structures, special effort and techniques are needed to control that complexity and make them understandable by humans, not simply machines. Taking this course will teach you such techniques, which are common to good software engineering design, independent of the programming language, and include building abstractions to hide details, separating specification from implementation and establishing conventional interfaces to allow the creation of standard modules. Programming practice is necessary to the course, and you'll be using Python as it is well-suited to understanding fundamental computing ideas and practices.

At course completionﾠyou will be able to analyse a problem and design and implement a computational solution to the problem.ﾠYou will make use of three major programming paradigms: structured, object-oriented and event-driven.

Learning outcomes

After successfully completing this course you should be able to:

Assessment

Assessment summary

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

In semester exam (Saturday)

• Identity Verified
• In-person

Mode

Written

Category

Examination

Weight

25%

Due date

In-semester Saturday

29/03/2025 - 12/04/2025

The In-Semester Exam will be held at 2pm on Saturday 12 April (Week 7)

Learning outcomes

L01, L03, L04, L05

Task description

Exam details

Submission guidelines

Deferral or extension

You may be able to defer this exam.

The In-Semester Saturday Deferred Exam will be held on Saturday 10th of May (Week 10).

Assignment 1

Mode

Written

Category

Computer Code

Weight

15%

Due date

2/05/2025 3:00 pm

Task description

Submission guidelines

Assignment submitted on-line via Gradescope. Students should submit their code regularly to Gradescope as they progress in the assignment.

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.

Detailed solutions will be released to students within 7 days.

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 (4:00pm) 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

Written

Category

Computer Code

Weight

20%

Due date

30/05/2025 3:00 pm

Learning outcomes

L01, L02, L03, L04, L05, L06

Task description

Submission guidelines

Assignment submitted on-line via Gradescope. Students should submit their code regularly to Gradescope as they progress in the assignment.

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.

Detailed solutions will be released to students within 7 days.

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 (4:00pm) 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.

End of semester exam

• Hurdle
• Identity Verified
• In-person

Mode

Written

Category

Examination

Weight

40%

Due date

End of Semester Exam Period

7/06/2025 - 21/06/2025

Learning outcomes

L01, L02, L03, L04, L05, L06

Task description

Hurdle requirements

Exam details

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.

Additional course grading information

A mark in this course is calculated from the following four assessments in this course:

1. Assessment 1 (A1) 

2. In-semester exam (EM)

3. Assessment 2 (A2)

4. End-of-semester Exam (EF)

Supposing A1, EM, A2, EF are percentages in [0%, 100%] then your mark is

MARK = MAX(M1, M2)

where

M1 = 0.15*A1 + 0.20*A2 + 0.25*EM + 0.40*EF

M2 = 0.15*A1 + 0.20*A2 + 0.10*EM + 0.55*EF

This means that poor performance on the in-semester exam can be mitigated by performing well on the final exam.

Your mark will be computed using two digits precision, then rounded to the nearest integer.

At the discretion of the course coordinator, marks for the assessment items may be adjusted upwards (uniformly across the class), but not downwards.

Supplementary assessment

Supplementary assessment is available for this course.

Additional assessment information

Use of AI

Assignment 1 and Assignment 2 evaluate 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

Blackboard

There are extensive video modules, readings, examples, contact exercises, assignments and other resources that can be accessed via Blackboard.

Online Material

Lecture related notes can be accessed via Blackboard. Lectures will be example driven demonstrating the application of the concepts covered in the weekly readings. You need to be prepared for the lectures for this course by having read the weekly notes beforehand. This course will make use of ShiFoo. ShiFoo is a programming exercise system that automatically checks your answers and gives you feedback.

Facilities

Practical work for this course will take place in PC labs or classrooms. If your practical session is in a classroom, you will need to bring a laptop computer with you to work in these sessions. Several slots have been booked for this course, when you will have priority in the lab. A demonstrator will be present to answer questions and help with any problems - this includes any problems you are having with any of the online material. You should be aware that you will need to do more work independently of the 2 hours per week that is set aside for practicals. The required software, libraries and documentation are on the machines in the PC labs and instructions for downloading for home use can be accessed via Blackboard. For details of the Occupational Health and Safety requirements of the labs, refer to the EECS Student Guide.

Handouts

Notes, assignments, solutions, etc. will be made available through Blackboard.

Distribution of Notices

Important notices will appear on Blackboard.

Ed discussion forum 

This course will use Ed Discussion forum.

Learning activities

The learning activities for this course are outlined below. Learn more about the learning outcomes that apply to this course.

Additional learning activity information

Students receive weekly, regular feedback about their general contract work through conversations with casual demonstrators and comparing with the solution and peers.

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:

• EECS School Guidelines for Students