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Unit outline_

COMP5348: Enterprise Scale Software Architecture

Semester 1, 2020 [Normal evening] - Camperdown/Darlington, Sydney

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
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None
Corequisites
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None
Prohibitions
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None
Assumed knowledge
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Experience with software development as covered in SOFT2412 or COMP9103 and also COMP2123 OR COMP2823 OR INFO1105 OR INFO1905 (or equivalent UoS from different institutions).

Available to study abroad and exchange students

No

Teaching staff

Coordinator Basem Suleiman, basem.suleiman@sydney.edu.au
Lecturer(s) Basem Suleiman, basem.suleiman@sydney.edu.au
Type Description Weight Due Length
Final exam Final exam
Written questions covering all lectures, labs and assessments.
60% Formal exam period 2 hours
Outcomes assessed: LO1 LO3 LO4 LO5 LO6
Skills-based evaluation Practical task 1
Preliminary modeling task - part of distributed computing task.
1% Week 03 n/a
Outcomes assessed: LO5
Skills-based evaluation Practical task 2
Individual-work practical task using technologies for distributed computing
4% Week 06 n/a
Outcomes assessed: LO5
Assignment Assignment 1
Paper-based exercises based on material of weeks 1-6
10% Week 07 n/a
Outcomes assessed: LO3 LO4 LO5 LO6
Assignment Assignment 2
Paper-based tasks on W7-W10 materials, & reflecting on labs experiences.
10% Week 11 n/a
Outcomes assessed: LO1 LO6 LO5 LO4
Assignment Group project
practical work integrating subsystems using communication technologies
15% Week 12 n/a
Outcomes assessed: LO1 LO2 LO4 LO5

Assessment summary

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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.

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:

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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.

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

You may only use generative AI and automated writing tools in assessment tasks if you are permitted to by your unit coordinator. If you do use these tools, you must acknowledge this in your work, either in a footnote or an acknowledgement section. The assessment instructions or unit outline will give guidance of the types of tools that are permitted and how the tools should be used.

Your final submitted work must be your own, original work. You must acknowledge any use of generative AI tools that have been used in the assessment, and any material that forms part of your submission must be appropriately referenced. For guidance on how to acknowledge the use of AI, please refer to the AI in Education Canvas site.

The unapproved use of these tools or unacknowledged use will be considered a breach of the Academic Integrity Policy and penalties may apply.

Studiosity is permitted unless otherwise indicated by the unit coordinator. The use of this service must be acknowledged in your submission as detailed on the Learning Hub’s Canvas page.

Outside assessment tasks, generative AI tools may be used to support your learning. The AI in Education Canvas site contains a number of productive ways that students are using AI to improve their learning.

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.

WK Topic Learning activity Learning outcomes
Week 01 Unit Introduction, Definition of the field; Nature of Software Architect's Role; Types of non-functional requirements ("ilities"); Layering; Application Architecture Lecture and tutorial (3 hr) LO1 LO2 LO3 LO4 LO5 LO6
Week 02 State and concurrency Lecture and tutorial (3 hr) LO1 LO2 LO3 LO4 LO5 LO6
Week 03 Distributed computing Lecture and tutorial (3 hr) LO1 LO2 LO3 LO4 LO5 LO6
Week 04 Distributed transactions Lecture and tutorial (3 hr) LO1 LO2 LO3 LO4 LO5 LO6
Week 05 Performance Lecture and tutorial (3 hr) LO1 LO2 LO3 LO4 LO5 LO6
Week 06 Message oriented middleware; assynchronous messaging and related technologies Lecture and tutorial (3 hr) LO1 LO2 LO3 LO4 LO5 LO6
Week 07 Service-oriented architecture; Web services Lecture and tutorial (3 hr) LO1 LO2 LO3 LO4 LO5 LO6
Week 08 RESTful Services Lecture and tutorial (3 hr) LO1 LO2 LO3 LO4 LO5 LO6
Week 09 Predicting performance; queuing theory Lecture and tutorial (3 hr) LO1 LO2 LO3 LO4 LO5 LO6
Week 10 Scalability and availability; fault-tolerance Lecture and tutorial (3 hr) LO1 LO2 LO3 LO4 LO5 LO6
Week 11 Cloud computing Lecture and tutorial (3 hr) LO1 LO2 LO3 LO4 LO5 LO6
Week 12 Industry speakers Lecture and tutorial (3 hr) LO1 LO2 LO3 LO4 LO5 LO6
Week 13 Revision and exam preparation Lecture and tutorial (3 hr) LO1 LO2 LO3 LO4 LO5 LO6

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 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. 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
GQ1 GQ2 GQ3 GQ4 GQ5 GQ6 GQ7 GQ8 GQ9

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

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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.