Outline

Overview

This unit covers topics on software architecture for large-scale enterprises. Computer systems for large-scale enterprises handle critical business processes, interact with computer systems of other organisations, and have to be highly reliable, available and scalable. This class of systems are built up from several application components, incorporating existing "legacy" code and data stores as well as linking these through middleware technologies, such as distributed transaction processing, remote objects, message-queuing, publish-subscribe, and clustering. The choice of middleware can decide whether the system achieves essential non- functional requirements such as performance and availability. The objective of this unit of study is to educate students for their later professional career and it covers Software Architecture topics of the ACM/IEEE Software Engineering curriculum. Objective: The objective of this unit of study is to educate students for their later professional career and it covers topics of the ACM/IEEE Software Engineering curriculum.

Unit details and rules

Academic unit	Computer Science
Credit points	6
Prerequisites ?	(DATA3888 or COMP3888 or COMP3988 or CSEC3888 or ISYS3888 or SOFT3888 or ENGG3112 or SCPU3001) and SOFT2412 and (COMP2123 or COMP2823 or INFO1105 or INFO1905)
Corequisites ?	None
Prohibitions ?	COMP5348
Assumed knowledge ?	A major in a computer science area
Available to study abroad and exchange students	Yes

Teaching staff

Coordinator	Wei Bao, wei.bao@sydney.edu.au
Lecturer(s)	Liming Ge, liming.ge@sydney.edu.au

Assessment

The census date for this unit availability is 1 September 2025

Details
Criteria

Type	Description	Weight	Due	Length	Use of AI
Written exam ?	Final exam Written questions covering all lectures, labs and assessments.	60%	Formal exam period	2 hours	AI prohibited
Outcomes assessed:
Practical skill	Practical task 1 Preliminary modeling task - part of distributed computing task.	1%	Week 04 Due date: 31 Aug 2025 at 23:59	—	AI allowed
Outcomes assessed:
Practical skill	Practical task 2 Individual-work practical task using technologies for distributed computing	4%	Week 06 Due date: 14 Sep 2025 at 23:59	—	AI allowed
Outcomes assessed:
Practical skill	Assignment 1 Paper-based exercises based on material of weeks 1-6.	10%	Week 07 Due date: 21 Sep 2025 at 23:59	—	AI allowed
Outcomes assessed:
Practical skill	Assignment 2 Paper-based tasks on W7-W10 materials, & reflecting on labs experiences.	10%	Week 11 Due date: 26 Oct 2025 at 23:59	—	AI allowed
Outcomes assessed:
Creative work	Group project Practical work integrating subsystems using communication technologies.	15%	Week 12 Due date: 02 Nov 2025 at 23:59	—	AI allowed
Outcomes assessed:
= hurdle task ? = group assignment ?

Assessment summary

The assessments aim to demonstrate the ability to design an enterprise software architecture, including essential skills in states, concurrency, transactions, distributed computing, middleware, performance evaluation, web development and cloud computing.

Practical task 1 is a preliminary modelling task covering weeks 2-3 (state, concurrency and distributed computing).

Practical task 2 is a distributed computing task covering weeks 3-4.

Assignment 1 is a paper-based assignment covering weeks 1-6.

Assignment 2 is paper based and covers weeks 7-10.

Group work is a subsystem integration project involving communication.

Final exam is in the form of written questions and covers all lectures, labs and assessments.

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 sydney.edu.au/students/guide-to-grades.

For more information see guide to grades.

Use of generative artificial intelligence (AI)

You can use generative AI tools for open assessments. Restrictions on AI use apply to secure, supervised assessments used to confirm if students have met specific learning outcomes.

Refer to the assessment table above to see if AI is allowed, for assessments in this unit and check Canvas for full instructions on assessment tasks and AI use.

If you use AI, you must always acknowledge it. Misusing AI may lead to a breach of the Academic Integrity Policy.

Visit the Current Students website for more information on AI in assessments, including details on how to acknowledge its use.

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.

Academic integrity

The University expects students to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.

Our website provides information on academic integrity and the resources available to all students. This includes advice on how to avoid common breaches of academic integrity. Ensure that you have completed the Academic Honesty Education Module (AHEM) which is mandatory for all commencing coursework students

Penalties for serious breaches can significantly impact your studies and your career after graduation. It is important that you speak with your unit coordinator if you need help with completing assessments.

Visit the Current Students website for more information on AI in assessments, including details on how to acknowledge its use.

Learning support

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 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. 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

Weekly schedule

WK	Topic	Learning activity
Week 01	Introduction	Lecture and tutorial (3 hr)
Week 02	State and concurrency	Lecture and tutorial (3 hr)
Week 03	Distributed computing	Lecture and tutorial (3 hr)
Week 04	Distributed transactions	Lecture and tutorial (3 hr)
Week 05	Performance	Lecture and tutorial (3 hr)
Week 06	Message oriented middleware and asynchronous technologies	Lecture and tutorial (3 hr)
Week 07	Service-oriented architecture and RESTful services	Lecture and tutorial (3 hr)
Week 08	Predicting performance and queues	Lecture and tutorial (3 hr)
Week 09	Scalability, availability and fault-tolerance	Lecture and tutorial (3 hr)
Week 10	Professional pathway towards software architect	Lecture and tutorial (3 hr)
Week 11	Software architecture in practice	Lecture and tutorial (3 hr)
Week 12	Cloud computing	Lecture and tutorial (3 hr)
Week 13	Review and exam preparation	Lecture and tutorial (3 hr)

Attendance and class requirements

Lectures: face-to-face and online lecture recording on Canvas.
Laboratory: Laboratory sessions are for students to practice problem-solving, application of the concepts, and use of technologies.
Independent study: Independent study is required for reading from sources, doing assignments, etc

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.

Required readings

Note: References are provided for guidance purposes only. Students are advised to consult these books in the university library. Purchase is not required.

Learning outcomes

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.

Outcomes
Graduate qualities

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

LO1. Produce written evaluation of different architectures and/or of different technologies.
LO2. Work in small teams of people with diverse skills and backgrounds, to complete demanding tasks which are loosely defined and require rapid learning of new concepts.
LO3. Understand the role of a software architect; respect what he/she is doing, and why; know when to involve him/her.
LO4. Recognise the relationship between different software architecture choices, and their impact on various non-functional attributes of the software.
LO5. Demonstrate broad knowledge of common architectural approaches for enterprise software, as well as detailed skills working with some technologies available to implement those approaches.
LO6. Carry out performance analysis, explain performance measurement principles, and identify suitable approaches for state management in face of concurrency.

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
Learning outcomes

Responding to student feedback

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

I have made adjustments to better align with the University's academic calendar and to improve the student experience. Specifically, the due dates for the assessments are adjusted to better align with the census date and holiday periods in the coming semester. Content is updated to cover the recent advances in software architecture.

Disclaimer

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

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

Current students

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Use of generative artificial intelligence (AI)

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Support for students

Weekly schedule

Weekly schedule

Attendance and class requirements

Study commitment

Required readings

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Disclaimer

On this page

Useful links

COMP4348: Enterprise Scale Software Architecture

Semester 2, 2025 [Normal evening] - Camperdown/Darlington, Sydney

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Use of generative artificial intelligence (AI)

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Support for students

Weekly schedule

Weekly schedule

Attendance and class requirements

Study commitment

Required readings

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Disclaimer

On this page

Useful links