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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 (login required)(opens in new window)
Contact information
Semester 1
Artem Polyvyanyy
artem.polyvyanyy@unimelb.edu.au
Overview
Availability | Semester 1 |
---|---|
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
On completion of this subject the student is expected to:
- Identify and abstract the key features of a range of complex system
- Apply the theoretical concepts 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
- 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: 8 April 2024
Eligibility and requirements
Prerequisites
Students must meet one of the following prerequisite options:
Option 1
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 |
COMP20007 | Design of Algorithms | Semester 1 (On Campus - Parkville) |
12.5 |
COMP90038 | Algorithms and Complexity |
Semester 1 (On Campus - Parkville)
Semester 2 (On Campus - Parkville)
|
12.5 |
Option 2
Admission into the MC-CS Master of Computer Science
Corequisites
Non-allowed subjects
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: 8 April 2024
Assessment
Description | Timing | Percentage |
---|---|---|
One research project (involving a programming task and report writing) executed individually by each student, expected to take approximately 25 - 30 hours. Intended Learning Outcomes (ILOs) 1-4 are addressed in this assessment.
| From Week 5 to Week 7 | 25% |
One research project (involving programming and report writing) executed in groups of up to three students. Requiring 25-30 hours of work for each student. ILOs 2-5 are addressed in this assessment.
| From Week 10 to Week 12 | 25% |
A written examination. ILOs 1-4 are addressed in this assessment.
| During the examination period | 50% |
Last updated: 8 April 2024
Dates & times
- Semester 1
Principal coordinator Artem Polyvyanyy Mode of delivery On Campus (Parkville) Contact hours 36 hours consisting of two 1-hour lectures and one 1-hour tutorial per week. Some computer lab classes will require you to bring your own device. Total time commitment 200 hours Teaching period 26 February 2024 to 26 May 2024 Last self-enrol date 8 March 2024 Census date 3 April 2024 Last date to withdraw without fail 3 May 2024 Assessment period ends 21 June 2024 Semester 1 contact information
Artem Polyvyanyy
artem.polyvyanyy@unimelb.edu.au
Time commitment details
200 hours
What do these dates mean
Visit this webpage to find out about these key dates, including how they impact on:
- Your tuition fees, academic transcript and statements.
- And for Commonwealth Supported students, your:
- Student Learning Entitlement. This applies to all students enrolled in a Commonwealth Supported Place (CSP).
Subjects withdrawn after the census date (including up to the ‘last day to withdraw without fail’) count toward the Student Learning Entitlement.
Last updated: 8 April 2024
Further information
- Texts
Prescribed texts
There are no specifically prescribed or recommended texts for this subject.
- Subject notes
LEARNING AND TEACHING METHODS
The subject will be delivered through a combination of lectures, hands-on workshops, individual assignments, and a team 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 Ph.D.- Engineering Course Master of Philosophy - Engineering Specialisation (formal) Software Specialisation (formal) Software with Business - 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.
- Available to Study Abroad and/or Study Exchange Students
This subject is available to students studying at the University from eligible overseas institutions on exchange and study abroad. Students are required to satisfy any listed requirements, such as pre- and co-requisites, for enrolment in the subject.
Last updated: 8 April 2024