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Unit of study_

COMP9001: Introduction to Programming

Semester 1, 2024 [Normal day] - Camperdown/Darlington, Sydney

This unit is an essential starting point for software developers, IT consultants, and computer scientists to build their understanding of principle computer operation. Students will obtain knowledge and skills with procedural programming. Crucial concepts include defining data types, control flow, iteration, functions, recursion, the model of addressable memory. Students will be able to reinterpret a general problem into a computer problem, and use their understanding of the computer model to develop source code. This unit trains students with software development process, including skills of testing and debugging. It is a prerequisite for more advanced programming languages, systems programming, computer security and high performance computing.

Unit details and rules

Unit code COMP9001
Academic unit Computer Science
Credit points 6
Prohibitions
? 
INFO1110 OR INFO1910 OR INFO1103 OR INFO1903 OR INFO1105 OR INFO1905 OR ENGG1810
Prerequisites
? 
None
Corequisites
? 
None
Assumed knowledge
? 

None

Available to study abroad and exchange students

Yes

Teaching staff

Coordinator John Stavrakakis, john.stavrakakis@sydney.edu.au
Lecturer(s) Hazem El-Alfy, hazem.elalfy@sydney.edu.au
Bob Kummerfeld, bob.kummerfeld@sydney.edu.au
Tutor(s) Tim Yarkov, tim.yarkov@sydney.edu.au
Type Description Weight Due Length
Supervised exam
? 
hurdle task
Final Examination
Pen and paper exam.
40% Formal exam period 2 hours
Outcomes assessed: LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO8 LO9 LO10 LO11
Participation Lab Participation
Short answer questions to be completed and evaluated with tutor during lab.
8% Multiple weeks 10 - 20 minutes
Outcomes assessed: LO1 LO11 LO10 LO9 LO8 LO7 LO6 LO5 LO4 LO3 LO2
Small test Test
Paper test in timetabled session labelled as Activity Group - Assessment.
10% Week 05
Due date: 22 Mar 2024 at 08:00
1 hour
Outcomes assessed: LO3 LO10 LO6 LO5 LO4
Assignment Assignment
Solve computer programming problems before due date.
30% Week 11
Due date: 09 May 2024 at 23:59
14 days
Outcomes assessed: LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO8 LO9 LO11
Online task Homework 1
Solve programming exercises before the end of the week.
4% Weekly
Due date: 07 Mar 2024 at 23:59

Closing date: 07 Mar 2024
~10-60 minutes
Outcomes assessed: LO3 LO10 LO5 LO4
Online task Homework 2
Solve programming exercises before the end of the week.
8% Weekly
Due date: 04 Apr 2024 at 23:59

Closing date: 04 Apr 2024
~10 - 60 minutes
Outcomes assessed: LO1 LO7 LO5 LO4 LO3 LO2
hurdle task = hurdle task ?

Assessment summary

Homework 1:

Programming exercises to be completed by the end of the week and no later than the closing date (7 March 2024, 23:59). No submissions will be accepted after the closing date. Students are expected to demonstrate their programs and answer questions related to these exercises in the lab participation assessments.

Homework 2:

Programming exercises to be completed by the end of the week and no later than the closing date (4 April 2024, 23:59) . No submissions will be accepted after the closing date. Students are expected to demonstrate their programs and answer questions related to these exercises in the lab participation assessments.

Lab Participation:

The best of 8 out of 13 will be selected for reporting of the marks. This will be marked and discuss in-class by the tutor.

Test:

Paper test that will require students to demonstrate knowledge in procedural programming which may cover reading and tracing through short programs, debugging and writing programs to solve a descriptive problem.

Assignment:

To be completed individually during the semester.  Assignments may require submission of code, flowcharts, tests, or reports. These will be assessed with test cases and manual grading. Format and submission details of assignments to be provided on release.

Final examination:

The final exam can cover any aspect of the course. Demonstrate knowledge in procedural programming. Reading and tracing through short programs. Writing short programs. Writing test cases and debugging with existing test cases. The final exam is a written examination held during the examination period.  Students must score a minimum of 40% to pass the unit.

Detailed information for each assessment can be found on the course website: edstem.org

Special consideration
Approved special consideration will be given these outcomes:

  • Homework 1 and Homework 2: Marks adjustment. Simple extension is not applicable.
  • Test: A new or varied evaluation will be granted if marks adjustments cannot be applied.
  • Lab participation:  Absence noted. Students are responsible for catching up with the contents. Simple extension is not applicable.
  • Assignment: An extension of time will be granted to complete the assignment. This assessment is eligible for simple extension. Marks adjustments cannot be granted for this component.

Conditions for the pass in this course:
- At least 50% total

- At least 40% in the Final Examination

Use of language translation tools for all online assessments is forbidden. All answers must be provided in the English language, including code comments.

Additionally, for this course, students may be asked for further development of their assessments if they fail to attend at least 80% of their labs.

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.

For more information see sydney.edu.au/students/guide-to-grades.

The tutor will provide feedback for the weekly tutorial and will provide further feedback to students about correctness, style and testing of their assignments.

Automatic testing provides further feedback.

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:

Late submissions are not accepted for any assessments unless an approved special consideration is granted.

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.

You may only use artificial intelligence and writing assistance tools in assessment tasks if you are permitted to by your unit coordinator, and if you do use them, you must also acknowledge this in your work, either in a footnote or an acknowledgement section.

Studiosity is permitted for postgraduate units unless otherwise indicated by the unit coordinator. The use of this service must be acknowledged in your submission.

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.

Support for students

The Support for Students Policy 2023 reflects the University’s commitment to supporting students in their academic journey and making the University safe for students. It is important that you read and understand this policy so that you are familiar with the range of support services available to you and understand how to engage with them.

The University uses email as its primary source of communication with students who need support under the Support for Students Policy 2023. Make sure you check your University email regularly and respond to any communications received from the University.

Learning resources and detailed information about weekly assessment and learning activities can be accessed via Canvas. It is essential that you visit your unit of study Canvas site to ensure you are up to date with all of your tasks.

If you are having difficulties completing your studies, or are feeling unsure about your progress, we are here to help. You can access the support services offered by the University at any time:

Support and Services (including health and wellbeing services, financial support and learning support)
Course planning and administration
Meet with an Academic Adviser

WK Topic Learning activity Learning outcomes
Week 01 Introduction to Programming. First program. Lecture (2 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO10 LO11
Getting started with programming basics Computer laboratory (2 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO10 LO11
Week 02 Variables and Data types Lecture (2 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO10 LO11
Variables and Data types Computer laboratory (2 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO10 LO11
Week 03 Conditionals Lecture (2 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO10 LO11
Conditionals Computer laboratory (2 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO10 LO11
Week 04 Iteration Lecture (2 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO10 LO11
Iteration Computer laboratory (2 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO10 LO11
Week 05 Flow of Execution. ​Functions​ Lecture (2 hr) LO1 LO3 LO4 LO5 LO6 LO10 LO11
Flow of Execution. ​Functions​ Computer laboratory (2 hr) LO1 LO3 LO4 LO5 LO6 LO10 LO11
Week 06 Collections Lecture (2 hr) LO1 LO2 LO3 LO5 LO6 LO9 LO10 LO11
Collections Computer laboratory (2 hr) LO1 LO2 LO3 LO5 LO6 LO9 LO10 LO11
Week 07 Classes and Objects Lecture (2 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO9 LO10 LO11
Classes and Objects Computer laboratory (2 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO9 LO10 LO11
Week 08 File I/O Lecture (2 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO9 LO10 LO11
File I/O Computer laboratory (2 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO9 LO10 LO11
Week 09 More Flow Control Lecture (2 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO9 LO10 LO11
More Flow Control Computer laboratory (2 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO9 LO10 LO11
Week 10 Testing Lecture (2 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO9 LO10 LO11
Testing Computer laboratory (2 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO9 LO10 LO11
Week 11 Recursion Lecture (2 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO8 LO9 LO10 LO11
Recursion Computer laboratory (2 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO8 LO9 LO10 LO11
Week 12 Iterators and Multidimensional arrays Lecture (2 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO9 LO10 LO11
Iterators and Multidimensional arrays Computer laboratory (2 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO9 LO10 LO11
Week 13 Revision Lecture (2 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO8 LO9 LO10 LO11
Revision Computer laboratory (2 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO8 LO9 LO10 LO11

Attendance and class requirements

Course websites:

Canvas and Ed are both used in this course for separate purposes. Students are encouraged to engage with the discussions and support on Ed for their learning.

Students are expected to regularly visit these websites to learn of announcements and information concerning format and schedule of assessment. Canvas is a website that will be used to disseminate the lecture recordings and for publishing of results.

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

All readings for this unit can be accessed through the Library eReserve, available on Canvas.

  • Downey, A. B. (2015). Think Python: How to Think Like a Computer Scientist (2e ed.). O’Reilly Media, Incorporated.

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. employ programming style conventions for writing consistently readable code
  • LO2. design and construct new functionality to existing procedural program or function
  • LO3. compose a structured algorithmic design to solve the descriptive problem specification
  • LO4. compose an entire procedural program from descriptive problem specification
  • LO5. demonstrate knowledge of programming principles, data types, variables and operators, control-flow: simple statement sequence, if-then-else, while functions, stack, input/output, reference memory model
  • LO6. compose, analyse and trace procedural code. Scoping/variable lifetime, memory of the stack, references and global's, data types, operations on data types
  • LO7. construct code cliches for input and manipulating arrays, including maximum, minimum, search or traverse, with actions on each element for counting or summation
  • LO8. construct and assess code for recursively-defined numerical functions, and for recursively described array manipulations
  • LO9. apply testing methods and assess programs through debugging and write a set of tests for a small program or function
  • LO10. explain compilation process and debugging mechanism
  • LO11. use standard library functions.

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.

Reduction of one pen-and-paper test to reduce assessment.

Every week students should:

  • Read the required sections of literature
  • Attend and take notes for the Live lecture (Mondays)
  • Watch and take notes for the Online lecture (via Canvas website)
  • Complete the weekly Lesson for Lecture
  • Prepare for the Labs by reviewing reading, lecture and tutorial questions 
  • Complete the weekly Labs before it commences
  • Attend and participate in weekly Labs with tutor (as timetabled)

Additionally:

  • Students should ask questions on Ed
  • Students should engage with their teacher for feedback in their Labs.

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.