Outline

Overview

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

Academic unit	Computer Science
Credit points	6
Prerequisites ?	None
Corequisites ?	None
Prohibitions ?	INFO1110 OR INFO1910 OR INFO1103 OR INFO1903 OR INFO1105 OR INFO1905 OR ENGG1810
Assumed knowledge ?	None
Available to study abroad and exchange students	Yes

Teaching staff

Coordinator	Sue Chng, sue.chng@sydney.edu.au
Lecturer(s)	Nazanin Borhan, nazanin.borhan@sydney.edu.au
Lecturer(s)	Bob Kummerfeld, bob.kummerfeld@sydney.edu.au
Tutor(s)	Ehab Ahmed, ehab.ahmed@sydney.edu.au
	Hamish Croser, hamish.croser@sydney.edu.au
	Joshua Blair, joshua.blair@sydney.edu.au

Type	Description	Weight	Due	Length
Supervised exam ?	Final Examination Pen and paper exam.	30%	Formal exam period	2 hours
Outcomes assessed:
Participation	Lab Participation Short answer questions to be completed and evaluated with tutor during lab.	8%	Multiple weeks	10 - 20 minutes
Outcomes assessed:
Small test	Test 1 Paper test in timetabled session labelled as Activity Group - Assessment.	10%	Week 05 Due date: 01 Sep 2023 at 08:30	1 hour
Outcomes assessed:
Small test	Test 2 Paper test in timetabled session labelled as Activity Group - Assessment.	10%	Week 10 Due date: 13 Oct 2023 at 08:30	1 hour
Outcomes assessed:
Assignment	Assignment Solve computer programming problems before due date.	30%	Week 12 Due date: 26 Oct 2023 at 23:59	14 days
Outcomes assessed:
Online task	Homework 1 Solve programming exercises before the end of the week.	4%	Weekly Due date: 13 Aug 2023 at 23:59 Closing date: 13 Aug 2023	~10-60 minutes
Outcomes assessed:
Attendance	Homework 2 Solve programming exercises before the end of the week.	8%	Weekly Due date: 10 Sep 2023 at 23:59 Closing date: 10 Sep 2023	~10 - 60 minutes
Outcomes assessed:

Assessment summary

Homework 1:

Programming exercises to be completed by the end of the week and no later than the closing date (13 August 2023, 23:59). No submissions will be accepted after this 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 (10 September 2023, 23:59) . No submissions will be accepted after this 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.

Tests:

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.

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 1 and Test 2: 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

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.

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.

Use of generative artificial intelligence (AI) and automated writing tools

You may only use generative AI and automated writing tools in assessment tasks if you are permitted to by your unit coordinator. If you do use these tools, you must acknowledge this in your work, either in a footnote or an acknowledgement section. The assessment instructions or unit outline will give guidance of the types of tools that are permitted and how the tools should be used.

Your final submitted work must be your own, original work. You must acknowledge any use of generative AI tools that have been used in the assessment, and any material that forms part of your submission must be appropriately referenced. For guidance on how to acknowledge the use of AI, please refer to the AI in Education Canvas site.

The unapproved use of these tools or unacknowledged use will be considered a breach of the Academic Integrity Policy and penalties may apply.

Studiosity is permitted unless otherwise indicated by the unit coordinator. The use of this service must be acknowledged in your submission as detailed on the Learning Hub’s Canvas page.

Outside assessment tasks, generative AI tools may be used to support your learning. The AI in Education Canvas site contains a number of productive ways that students are using AI to improve their learning.

Learning support

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.

Weekly schedule

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

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

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.

Outcomes
Graduate qualities

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
Learning outcomes

Responding to student feedback

This section outlines changes made to this unit following staff and student reviews.

Assessments are updated for in-person delivery. Assignment 1 is changed into continuous assessment with small weights distributed across the weeks in the first half of the semester.

Additional information

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.

Access to course contents: Lecture, Tutorial Access to discussion and support forum.

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.

Current students

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Weekly schedule

Weekly schedule

Attendance and class requirements

Study commitment

Required readings

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Additional information

Additional information

Disclaimer

On this page

Useful links

Media

Student links

About us

Connect

Current students

COMP9001: Introduction to Programming

Semester 2, 2023 [Normal day] - Camperdown/Darlington, Sydney

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Weekly schedule

Weekly schedule

Attendance and class requirements

Study commitment

Required readings

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Additional information

Additional information

Disclaimer

On this page

Useful links

Media

Student links

About us

Connect