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Modelling Complex Software Systems (SWEN90004)
Graduate courseworkPoints: 12.5On Campus (Parkville)
About this subject
- Overview
- Eligibility and requirements
- Assessment
- Dates and times
- Further information
- Timetable(opens in new window)
Contact information
Semester 1
Overview
Availability | Semester 1 |
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Fees | Look up fees |
AIMS
Mathematical modelling is important for understanding and engineering many facets of complex systems. The aim of this subject is for students to understand the range and use of mathematical theories and notations in the analysis of discrete systems, how to abstract the key aspects of a problem into a model to handle complexity, and how models can be employed to verify large-scale complex software systems.
INDICATIVE CONTENT
Topics covered will be selected from: Deterministic and stochastic modelling; dynamical systems; cellular automata; agent-based modelling; complex networks; simulation and analysis of complex systems; concurrent systems modelling, analysis and implementation; process algebra; temporal logic and model checking.
Intended learning outcomes
INTENDED LEARNING OUTCOMES (ILO)
On completion of this subject the student is expected to:
- Identify and abstract the key features of a range of complex system
- Understand the theoretical basis underpinning the analysis of complex systems
- Analyse models of discrete and concurrent systems using a range of modern techniques
- Evaluate and select, amongst different modelling techniques, the most appropriate for analysing specific systems
- Create mathematical/computational models to analyse and verify the behaviour of complex systems.
Generic skills
On completion of this subject, students should have the following skills.
• Ability to undertake problem identification, formulation and solution
• Ability to utilise a systems approach to analysing software properties
• Capacity for independent critical analysis of models, and self-directed research for mathematical modelling approaches
• Intellectual curiosity and creativity, including understanding of the philosophical and methodological ideas behind research in software systems analysis
• Openness to new ideas and unconventional critiques of received wisdom
Last updated: 3 November 2022
Eligibility and requirements
Prerequisites
One of the following:
COMP20004 Discrete Structures
Code | Name | Teaching period | Credit Points |
---|---|---|---|
COMP30026 | Models of Computation | Semester 2 (On Campus - Parkville) |
12.5 |
And one of:
Code | Name | Teaching period | Credit Points |
---|---|---|---|
COMP20003 | Algorithms and Data Structures | Semester 2 (On Campus - Parkville) |
12.5 |
COMP90038 | Algorithms and Complexity |
Semester 2 (On Campus - Parkville)
Semester 1 (On Campus - Parkville)
|
12.5 |
Corequisites
None
Non-allowed subjects
Students cannot enrol in and gain credit for this subject and:
433-441 Systems Modelling and Analysis
433-641 Systems Modelling and Analysis
SWEN40004 Modelling Complex Software Systems
Inherent requirements (core participation requirements)
The University of Melbourne is committed to providing students with reasonable adjustments to assessment and participation under the Disability Standards for Education (2005), and the Assessment and Results Policy (MPF1326). Students are expected to meet the core participation requirements for their course. These can be viewed under Entry and Participation Requirements for the course outlines in the Handbook.
Further details on how to seek academic adjustments can be found on the Student Equity and Disability Support website: http://services.unimelb.edu.au/student-equity/home
Last updated: 3 November 2022
Assessment
Additional details
- One research project (involving a programming task and report writing) executed in pairs, expected to take approximately 25-30 hours, due in week 6 (20)%
- One assignment (in two parts) expected to take approximately 25-30 hours, due in weeks 10 and 12 (20)%
- A 3-hour closed-book written examination, end of semester examination period (60)%
Hurdle requirement: To pass the subject, the student must obtain:
- at least 50% overall;
- at least 50% (20/40) in project work; and
- at least 50% (30/60) in the written examination
Intended Learning Outcomes (ILOs) 1 to 4 are addressed in the examination
ILOs 2, 3, ad 4 are addressed in the assignments, and the pair research project
Generic skills are addressed by all assessment items
Last updated: 3 November 2022
Dates & times
- Semester 1
Principal coordinator Nic Geard Mode of delivery On Campus (Parkville) Contact hours 36 hours. 3 hours per week. Total time commitment 200 hours Teaching period 27 February 2017 to 28 May 2017 Last self-enrol date 10 March 2017 Census date 31 March 2017 Last date to withdraw without fail 5 May 2017 Assessment period ends 23 June 2017 Semester 1 contact information
Time commitment details
200 hours.
Last updated: 3 November 2022
Further information
- Texts
Prescribed texts
None
Recommended texts and other resources
None
- Subject notes
LEARNING AND TEACHING METHODS
The subject will be delivered through a combination of lectures, hands-on workshops, individual assignments, and a pair-based project in which students use modelling and simulation to study a complex system.
INDICATIVE KEY LEARNING RESOURCES
A package of notes will be made available to the students at the start of the course. An addition reference is: Kramer, Jeff, and Jeff Magee: Concurrency: State Models and Java Programs, John Wiley and Sons, 2nd edition (2006).
CAREERS / INDUSTRY LINKS
The ability for software engineers and computer scientists to abstract and analyse complex problems is key to their profession. As software systems continue to be deployed in increasingly complex and critical environments, such as transport control, manufacturing, and healthcare, the tools and methods for analysing complex systems will become more important.
- Related Handbook entries
This subject contributes to the following:
Type Name Course Doctor of Philosophy - Engineering Course Master of Philosophy - Engineering Course Master of Information Technology Course Master of Information Technology Course Ph.D.- Engineering Specialisation (formal) Software with Business Major MIT Computing Specialisation Informal specialisation Master of Engineering (Software) Specialisation (formal) Software Informal specialisation Master of Engineering (Software with Business) Specialisation (formal) Computing - Available through the Community Access Program
About the Community Access Program (CAP)
This subject is available through the Community Access Program (also called Single Subject Studies) which allows you to enrol in single subjects offered by the University of Melbourne, without the commitment required to complete a whole degree.
Entry requirements including prerequisites may apply. Please refer to the CAP applications page for further information.
Additional information for this subject
Subject coordinator approval required
Last updated: 3 November 2022