ELEC5618: Semester 1, 2025
Skip to main content
Unit outline_

ELEC5618: Software Quality Engineering

Semester 1, 2025 [Normal day] - Camperdown/Darlington, Sydney

This unit will cover software quality planning, validation and verification methods and techniques, risk analysis, software review techniques, software standards and software process improvement and software reliability. Students who successfully complete this unit will understand the fundamental concepts of software quality engineering and be able to define software quality requirements, assess the quality of a software design, explain specific methods of building software quality, understand software reliability models and metrics, develop a software quality plan, understand quality assurance and control activities and techniques, understand various testing techniques including being able to verify and test a unit of code and comprehend ISO standards, SPICE, CMM and CMMI.

Unit details and rules

Academic unit School of Electrical and Computer Engineering
Credit points 6
Prerequisites
? 
None
Corequisites
? 
None
Prohibitions
? 
None
Assumed knowledge
? 

Writing programs with multiple functions or methods in multiple files; design of complex data structures and combination in non trivial algorithms; use of an integrated development environment; software version control systems

Available to study abroad and exchange students

Yes

Teaching staff

Coordinator Huaming Chen, huaming.chen@sydney.edu.au
Lecturer(s) Huaming Chen, huaming.chen@sydney.edu.au
Tutor(s) Yanli Li, yanli.li@sydney.edu.au
Nan Yang, n.yang@sydney.edu.au
JIAWEN WEN, jiawen.wen@sydney.edu.au
The census date for this unit availability is 31 March 2025
Type Description Weight Due Length
Supervised exam
? 
Final exam
It is a close book exam.
50% Formal exam period 2 hours
Outcomes assessed: LO3 LO4 LO5 LO1 LO6 LO7 LO8
Assignment group assignment AI Allowed Assignment 1
Project report 1
15% Week 06
Due date: 04 Apr 2025 at 23:59
Please refer to the canvas site.
Outcomes assessed: LO3 LO4 LO5 LO1 LO8
Online task AI Allowed Quiz
Mid-term quiz in week 8
5% Week 08
Due date: 17 Apr 2025 at 23:59
One hour
Outcomes assessed: LO3 LO7 LO6 LO1
Assignment AI Allowed Assignment 2
project report and presentation
30% Week 13
Due date: 01 Jun 2025 at 23:59
n/a
Outcomes assessed: LO2 LO9 LO4 LO7 LO8
group assignment = group assignment ?
AI allowed = AI allowed ?

Assessment summary

Detailed information for each assessment can be found on Canvas.

Assessment criteria

The University awards common result grades, set out in the Coursework Policy 2014 (Schedule 1).

As a general guide, a high distinction indicates work of an exceptional standard, a distinction a very high standard, a credit a good standard, and a pass an acceptable standard.

Result name

Mark range

Description

High distinction

85 - 100

 

Distinction

75 - 84

 

Credit

65 - 74

 

Pass

50 - 64

 

Fail

0 - 49

When you don’t meet the learning outcomes of the unit to a satisfactory standard.

For more information see guide to grades.

Use of generative artificial intelligence (AI) and automated writing tools

Except for supervised exams or in-semester tests, you may use generative AI and automated writing tools in assessments unless expressly prohibited by your unit coordinator. 

For exams and in-semester tests, the use of AI and automated writing tools is not allowed unless expressly permitted in the assessment instructions. 

The icons in the assessment table above indicate whether AI is allowed – whether full AI, or only some AI (the latter is referred to as “AI restricted”). If no icon is shown, AI use is not permitted at all for the task. Refer to Canvas for full instructions on assessment tasks for this unit. 

Your final submission must be your own, original work. You must acknowledge any use of automated writing tools or generative AI, and any material generated that you include in your final submission must be properly referenced. You may be required to submit generative AI inputs and outputs that you used during your assessment process, or drafts of your original work. Inappropriate use of generative AI is considered a breach of the Academic Integrity Policy and penalties may apply. 

The Current Students website provides information on artificial intelligence in assessments. For help on how to correctly acknowledge the use of AI, please refer to the  AI in Education Canvas site

Late submission

In accordance with University policy, these penalties apply when written work is submitted after 11:59pm on the due date:

  • Deduction of 5% of the maximum mark for each calendar day after the due date.
  • After ten calendar days late, a mark of zero will be awarded.

This unit has an exception to the standard University policy or supplementary information has been provided by the unit coordinator. This information is displayed below:

5% per day

Academic integrity

The Current Student website provides information on academic integrity and the resources available to all students. The University expects students and staff to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.

We use similarity detection software to detect potential instances of plagiarism or other forms of academic integrity breach. If such matches indicate evidence of plagiarism or other forms of academic integrity breaches, your teacher is required to report your work for further investigation.

Simple extensions

If you encounter a problem submitting your work on time, you may be able to apply for an extension of five calendar days through a simple extension.  The application process will be different depending on the type of assessment and extensions cannot be granted for some assessment types like exams.

Special consideration

If exceptional circumstances mean you can’t complete an assessment, you need consideration for a longer period of time, or if you have essential commitments which impact your performance in an assessment, you may be eligible for special consideration or special arrangements.

Special consideration applications will not be affected by a simple extension application.

Using AI responsibly

Co-created with students, AI in Education includes lots of helpful examples of how students use generative AI tools to support their learning. It explains how generative AI works, the different tools available and how to use them responsibly and productively.

Support for students

The Support for Students Policy 2023 reflects the University’s commitment to supporting students in their academic journey and making the University safe for students. It is important that you read and understand this policy so that you are familiar with the range of support services available to you and understand how to engage with them.

The University uses email as its primary source of communication with students who need support under the Support for Students Policy 2023. Make sure you check your University email regularly and respond to any communications received from the University.

Learning resources and detailed information about weekly assessment and learning activities can be accessed via Canvas. It is essential that you visit your unit of study Canvas site to ensure you are up to date with all of your tasks.

If you are having difficulties completing your studies, or are feeling unsure about your progress, we are here to help. You can access the support services offered by the University at any time:

Support and Services (including health and wellbeing services, financial support and learning support)
Course planning and administration
Meet with an Academic Adviser

WK Topic Learning activity Learning outcomes
Week 01 Course description and scenario Lecture (2 hr) LO1
Literature readings, research&review, projects Independent study (6 hr) LO1 LO2 LO3 LO9
Week 02 Software quality in a company Lecture and tutorial (4 hr) LO1 LO3 LO6 LO7
Literature readings, research&review, projects Independent study (6 hr) LO1 LO2 LO3
Week 03 Software quality planning, assurance and control Lecture and tutorial (4 hr) LO1 LO2 LO3 LO5 LO6 LO7
Literature readings, research&review, projects Independent study (6 hr) LO1 LO2 LO3
Week 04 Software requirement specification and use cases Lecture and tutorial (4 hr) LO1 LO2 LO3 LO4 LO5 LO6
Literature readings, research&review, projects Independent study (6 hr) LO1 LO2 LO4 LO5
Week 05 Verification vs. validation Lecture and tutorial (4 hr) LO1 LO2 LO3 LO7
Literature readings, research&review, projects Independent study (6 hr) LO1 LO2 LO4 LO5
Week 06 Software testing Lecture and tutorial (4 hr) LO6 LO7 LO8 LO9
Literature readings, research&review, projects Independent study (6 hr) LO1 LO2 LO4 LO5
Week 07 The software test plan Lecture and tutorial (4 hr) LO4 LO5 LO6 LO8 LO9
Literature readings, research&review, projects Independent study (6 hr) LO1 LO2 LO4 LO5 LO6 LO9
Week 08 Tools for testing Lecture and tutorial (4 hr) LO6 LO7 LO8 LO9
Literature readings, research&review, projects Independent study (6 hr) LO1 LO2 LO4 LO5 LO6 LO9
Week 09 SQE in agile environments Lecture and tutorial (4 hr) LO5 LO6 LO7 LO8 LO9
Literature readings, research&review, projects Independent study (6 hr) LO6 LO7 LO8 LO9
Week 10 Practical case study 1 Lecture and tutorial (4 hr) LO6 LO7 LO8 LO9
Literature readings, research&review, projects Independent study (6 hr) LO6 LO7 LO8 LO9
Week 11 Design a weekly agile cycle Lecture and tutorial (4 hr) LO3 LO4 LO5 LO7 LO9
Literature readings, research&review, projects Independent study (6 hr) LO2 LO6 LO7 LO8 LO9
Week 12 Practical case study 2 Lecture and tutorial (4 hr) LO6 LO7 LO8 LO9
Literature readings, research&review, projects Independent study (6 hr) LO2 LO6 LO7 LO8 LO9
Week 13 Course revision Lecture and tutorial (4 hr) LO2 LO3 LO5 LO7 LO9
Literature readings, research&review, projects Independent study (6 hr) LO2 LO3 LO5 LO7

Study commitment

Typically, there is a minimum expectation of 1.5-2 hours of student effort per week per credit point for units of study offered over a full semester. For a 6 credit point unit, this equates to roughly 120-150 hours of student effort in total.

Learning outcomes are what students know, understand and are able to do on completion of a unit of study. They are aligned with the University's graduate qualities and are assessed as part of the curriculum.

At the completion of this unit, you should be able to:

  • LO1. Demonstrate an understanding of the nature of risk in general terms, to the extent of the material presented
  • LO2. Produce reports to communicate and argue the importance of test strategy, procedures and activities in software development, using clear and concise language at a level appropriate with the expected aptitude of the stakeholders
  • LO3. Demonstrate an understanding of QA processes with respect to software development as part of professional practice and the adherence to standards
  • LO4. Develop QA tasks by using a clearly defined approach in addressing all of the quality factors and risks that may impede or otherwise affect the resulting software development
  • LO5. Use QA procedures to improve the development quality and efficiency of specific engineering projects, drawing on the concepts and principles developed and presented throughout the course
  • LO6. Recognise the benefits of QA procedures in design, implementation and operation of software systems at a professional standard in line with professional practice to the extent of the material presented
  • LO7. Demonstrate an understanding of the review process of software development using tools and techniques presented
  • LO8. Use simple models to describe and analyse the benefit of performing/not performing various testing and review tasks.
  • LO9. Work together to design and implement a test strategy and communicate the results in professional manners

Graduate qualities

The graduate qualities are the qualities and skills that all University of Sydney graduates must demonstrate on successful completion of an award course. As a future Sydney graduate, the set of qualities have been designed to equip you for the contemporary world.

GQ1 Depth of disciplinary expertise

Deep disciplinary expertise is the ability to integrate and rigorously apply knowledge, understanding and skills of a recognised discipline defined by scholarly activity, as well as familiarity with evolving practice of the discipline.

GQ2 Critical thinking and problem solving

Critical thinking and problem solving are the questioning of ideas, evidence and assumptions in order to propose and evaluate hypotheses or alternative arguments before formulating a conclusion or a solution to an identified problem.

GQ3 Oral and written communication

Effective communication, in both oral and written form, is the clear exchange of meaning in a manner that is appropriate to audience and context.

GQ4 Information and digital literacy

Information and digital literacy is the ability to locate, interpret, evaluate, manage, adapt, integrate, create and convey information using appropriate resources, tools and strategies.

GQ5 Inventiveness

Generating novel ideas and solutions.

GQ6 Cultural competence

Cultural Competence is the ability to actively, ethically, respectfully, and successfully engage across and between cultures. In the Australian context, this includes and celebrates Aboriginal and Torres Strait Islander cultures, knowledge systems, and a mature understanding of contemporary issues.

GQ7 Interdisciplinary effectiveness

Interdisciplinary effectiveness is the integration and synthesis of multiple viewpoints and practices, working effectively across disciplinary boundaries.

GQ8 Integrated professional, ethical, and personal identity

An integrated professional, ethical and personal identity is understanding the interaction between one’s personal and professional selves in an ethical context.

GQ9 Influence

Engaging others in a process, idea or vision.

Outcome map

Learning outcomes Graduate qualities
GQ1 GQ2 GQ3 GQ4 GQ5 GQ6 GQ7 GQ8 GQ9

This section outlines changes made to this unit following staff and student reviews.

LO, assessments and relevant staff information are updated in this version.

Disclaimer

The University reserves the right to amend units of study or no longer offer certain units, including where there are low enrolment numbers.

This unit of study outline was last modified on 09 Feb 2025.

To help you understand common terms that we use at the University, we offer an online glossary.