Modelling Complex Software Systems (SWEN90004)

Graduate courseworkPoints: 12.5Dual-Delivery (Parkville)

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Overview

Availability
Semester 1 - Dual-Delivery
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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
  • 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

  • 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: 31 January 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 (Dual-Delivery - Parkville)
 12.5

AND

One of

Code Name Teaching period Credit Points
COMP20003 Algorithms and Data Structures
Semester 2 (Dual-Delivery - Parkville)
 12.5
COMP20007 Design of Algorithms
Semester 1 (Dual-Delivery - Parkville)
 12.5
COMP90038 Algorithms and Complexity
Semester 1 (Dual-Delivery - Parkville)
Semester 2 (Dual-Delivery - Parkville)
 12.5

Option 2

Admission into the MC-CS Master of Computer Science

Corequisites

None

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: 31 January 2024

Assessment

DescriptionTimingPercentage

One research project (involving a programming task and report writing) executed in pairs, expected to take approximately 25 - 30 hours. Intended Learning Outcomes (ILO's) 2, 3, ad 4 are addressed in the research project.

  • 25-30 hours (of work required)
Hurdle requirement: To pass the subject, the student must obtain: at least 50% overall, and at least 50% (20/40) in project work.		Week 620%

One assignment (in two parts) expected to take approximately 25 - 30 hours, due in weeks 10 and 12. ILO's 2, 3, and 4 are addressed in the assignments.

  • 25-30 hours (of work required)
Hurdle requirement: To pass the subject, the student must obtain: at least 50% overall, and at least 50% (20/40) in project work.		From Week 10 to Week 1220%

A closed-book written examination. ILO's 1 to 4 are addressed in the examination.

  • 3 hours
Hurdle requirement: To pass the subject, the student must obtain: at least 50% overall, and at least 50% (30/60) in the written examination.		During the examination period60%

Last updated: 31 January 2024

Dates & times

  • Semester 1
    Principal coordinatorArtem Polyvyanyy
    Mode of deliveryDual-Delivery (Parkville)
    Contact hours36 hours. 3 hours per week
    Total time commitment200 hours
    Teaching period28 February 2022 to 29 May 2022
    Last self-enrol date11 March 2022
    Census date31 March 2022
    Last date to withdraw without fail 6 May 2022
    Assessment period ends24 June 2022

    Semester 1 contact information

    Artem Polyvyanyy

    artem.polyvyanyy@unimelb.edu.au

Time commitment details

200 hours

Last updated: 31 January 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 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:

    TypeName
    CoursePh.D.- Engineering
    CourseDoctor of Philosophy - Engineering
    CourseMaster of Philosophy - Engineering
    Specialisation (formal)Software with Business
    Specialisation (formal)Computing
    Specialisation (formal)Software
  • 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.

    Please note Single Subject Studies via Community Access Program is not available to student visa holders or applicants

    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: 31 January 2024