Engineering Computation

Subject COMP20005 (2015)

Note: This is an archived Handbook entry from 2015.

Credit Points: 12.5
Level: 2 (Undergraduate)
Dates & Locations:

This subject has the following teaching availabilities in 2015:

Semester 1, Parkville - Taught on campus.
Pre-teaching Period Start not applicable
Teaching Period 02-Mar-2015 to 31-May-2015
Assessment Period End 26-Jun-2015
Last date to Self-Enrol 13-Mar-2015
Census Date 31-Mar-2015
Last date to Withdraw without fail 08-May-2015

Semester 2, Parkville - Taught on campus.
Pre-teaching Period Start not applicable
Teaching Period 27-Jul-2015 to 25-Oct-2015
Assessment Period End 20-Nov-2015
Last date to Self-Enrol 07-Aug-2015
Census Date 31-Aug-2015
Last date to Withdraw without fail 25-Sep-2015

Timetable can be viewed here. For information about these dates, click here.
Time Commitment: Contact Hours: 60 hours, comprising of three 1-hour lectures and one 2-hour workshop per week
Total Time Commitment:

170 hours


One of the following:

Study Period Commencement:
Credit Points:
Semester 1, Semester 2
Semester 1, Semester 2

Plus one of:
(these may be taken concurrently)

620 156 Linear Algebra

620 157 Accelerated Mathematics 1

620 158 Accelerated Mathematics 2

Study Period Commencement:
Credit Points:
Summer Term, Semester 1, Semester 2


Admission to the MC-ENG Master of Engineering



Recommended Background Knowledge:
Study Period Commencement:
Credit Points:
Summer Term, Semester 2
Non Allowed Subjects:

Students cannot enrol in and gain credit for this subject and:

433 171 Introduction to Programming

433 151 Introduction to Programming (Advanced)

Core Participation Requirements:

For the purposes of considering request for Reasonable Adjustments under the Disability Standards for Education (Cwth 2005), and Student Support and Engagement Policy, academic requirements for this subject are articulated in the Subject Overview, Learning Outcomes, Assessment and Generic Skills sections of this entry.

It is University policy to take all reasonable steps to minimise the impact of disability upon academic study, and reasonable adjustments will be made to enhance a student's participation in the University's programs. Students who feel their disability may impact on meeting the requirements of this subject are encouraged to discuss this matter with a Faculty Student Adviser and Student Equity and Disability Support:


Assoc Prof Michael Kirley, Prof Alistair Moffat


Semester 1: Professor Alistair Moffat


Semester 2: Dr Michael Kirley


Subject Overview:


Many engineering disciplines make use of numerical solutions to computational problems. In this subject students will be introduced to the key elements of programming in a high level language, and will then use that skill to explore methods for solving numerical problems in a range of discipline areas.


  • Algorithmic problem solving
  • Fundamental data types: numbers and characters
  • Approximation and errors in numerical computation
  • Fundamental program structures: sequencing, selection, repetition, functions
  • Simple data storage structures, variables, arrays, and structures
  • Roots of equations and of linear algebraic equations
  • Curve fitting and splines
  • Interpolation and extrapolation
  • Numerical differentiation and integration.
Learning Outcomes:


On completion of this subject the student is expected to:

  1. Read, write and debug typical small-scale numerical programs in a high-level programming language such as C
  2. Test and debug such programs
  3. Argue for the correctness of such programs, from both a logical point of view and a numeric-soundness point of view
  4. Be aware of the range of tools available for creating computational solutions to engineering problems, and be able to evaluate and choose between alternative approaches
  5. Describe and employ the general concepts that apply when computers are used to solve mathematical problems
  6. Demonstrate familiarity with the underlying theory behind a range of numerical algorithms used in commercial engineering software packages
  • Project work during semester, requiring approximately 30 - 35 hours of work (30%), due in approximately Week 8 and Week 11
  • One mid-semester test (10%), held in Week 5 or Week 6
  • One two-hour end-of-semester examination (60%).

Hurdle requirement: To pass the subject, students must obtain at least:

  • 50% overall
  • 12/30 in project work
  • 28/70 in the mid-semester test and end-of-semester written examination combined.

Intended Learning Outcome (ILO) 1 is addressed in all components of assessment. ILO 2 is assessed in the programming assignments. ILO 3 is assessed in the programming assignments and in the examination. ILOs 4-6 are assessed in the examination.

Prescribed Texts:


Breadth Options:

This subject potentially can be taken as a breadth subject component for the following courses:

You should visit learn more about breadth subjects and read the breadth requirements for your degree, and should discuss your choice with your student adviser, before deciding on your subjects.

Fees Information: Subject EFTSL, Level, Discipline & Census Date
Generic Skills:

On completion of this subject students should have developed the following skills:

  • The ability to undertake problem identification, formulation and solution
  • Capacity for independent critical thought, rational inquiry and self-directed learning
  • Profound respect for truth and intellectual integrity, and for the ethics of scholarship
  • An ability to apply knowledge of basic science and engineering fundamentals.


The subject will be delivered through a combination of lectures, programming workshops, and programming exercises. Students will also be expected to develop and submit for assessment programming assignments.


Students will have access to lecture notes and lecture slides, and will be expected to own a copy of the textbook, nominated by the coordinator. Other guidance will be provided via LMS.


Programming competencies are a critical part of a range of engineering career pathways, especially electrical and mechanical engineering. Being familiar with computational thinking and problem solving techniques is important to the development of new devices and technologies in these disciplines.

Related Majors/Minors/Specialisations: B-ENG Electrical Engineering stream
B-ENG Mechanical Engineering stream
Environments Discipline subjects
Geomatics (Geomatic Engineering) major
Master of Engineering (Electrical with Business)
Master of Engineering (Electrical)
Master of Engineering (Mechanical with Business)
Master of Engineering (Mechanical)
Master of Engineering (Mechatronics)
Master of Engineering (Software with Business)
Master of Engineering (Software)
Master of Engineering (Spatial)
Science-credited subjects - new generation B-SCI and B-ENG.
Selective subjects for B-BMED
Spatial Systems

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