Outline

Overview

The unit introduces principles and concepts of modern computer systems, including mobile computers and the Internet, to provide students with fundamental knowledge of the environments in which modern, networked applications operate. Students will have basic knowledge to understand how computers work and are aware of principles and concepts they are likely to encounter in their career. The unit covers: Principles of operating systems and the way applications interact with the OS, including the particularities of modern operating systems for mobile devices Principles of computer networking, including mobile networking Writing applications that use facilities of the OS and networking, including understanding the challenges that are common in distributed systems

Unit details and rules

Academic unit	Computer Science
Credit points	6
Prerequisites ?	None
Corequisites ?	ELEC1601 and (INFO1110 or INFO1910 or INFO1103 or INFO1113)
Prohibitions ?	None
Assumed knowledge ?	A basic knowledge of Python is assumed. For most students, INFO1110 should have already been passed in Semester 1
Available to study abroad and exchange students	Yes

Teaching staff

Coordinator	Nguyen Tran, nguyen.tran@sydney.edu.au
Lecturer(s)	Alan Fekete, alan.fekete@sydney.edu.au
Lecturer(s)	Hazem El-Alfy, hazem.elalfy@sydney.edu.au

Assessment

The census date for this unit availability is 1 September 2025

Details
Criteria

Type	Description	Weight	Due	Length	Use of AI
Written exam ?	Final Exam Final Exam	40%	Formal exam period	2 hours	AI prohibited
Outcomes assessed:
Out-of-class quiz	Quizzes Weekly quizzes on basic concepts	10%	Multiple weeks	1 week	AI allowed
Outcomes assessed:
Practical skill	Homework 1 #earlyfeedbacktask. Testing your knowledge of Unix commands so far.	5%	Week 03 Due date: 24 Aug 2025 at 23:59	1 week	AI allowed
Outcomes assessed:
Practical skill	Homework 2 Periodic homework to test Unix knowledge	5%	Week 05 Due date: 07 Sep 2025 at 23:59	1 week	AI allowed
Outcomes assessed:
Creative work	Assignment 1 Programming task - Introductory Unix / Assembler	15%	Week 06 Due date: 14 Sep 2025 at 23:59 Closing date: 05 Dec 2025	3 weeks	AI allowed
Outcomes assessed:
Practical skill	Homework 3 Periodic homework to test Unix knowledge	5%	Week 08 Due date: 28 Sep 2025 at 23:59	1 week	AI allowed
Outcomes assessed:
Creative work	Assignment 2 Programming task - Networking Concepts	15%	Week 11 Due date: 26 Oct 2025 at 23:59 Closing date: 05 Dec 2025	3 weeks	AI allowed
Outcomes assessed:
Creative work	Assignment 3 Final Exam Practice	5%	Week 12 Due date: 02 Nov 2025 at 23:59 Closing date: 05 Dec 2025	1 week	AI allowed
Outcomes assessed:
= hurdle task ? = early feedback task ?

Early feedback task

This unit includes an early feedback task, designed to give you feedback prior to the census date for this unit. Details are provided in the Canvas site and your result will be recorded in your Marks page. It is important that you actively engage with this task so that the University can support you to be successful in this unit.

Assessment summary

Homework 1, due in week 3, is part of the Early Feedback Task.
Final Exam (pen and paper) during the examination period.

Detailed information for each assessment and due dates will be posted on Canvas.

Special consideration:
Approved special consideration will result in the following outcomes:

Homework and Quizzes: Mark adjustment. No simple extension for homework or quizzes. No late submissions.
Assignments: Extension of time. Assignments are eligible for simple extensions. Mark adjustments cannot be granted for assignments. No late submissions.

Conditions for passing this unit:

At least 50% of the total mark.
At least 40% in the final examination.

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.

Result name	Mark range	Description
High distinction	85 - 100
Distinction	75 - 84
Credit	65 - 74
Pass	50 - 64
Fail	0 - 49	It is a policy of the School of Computer Science that in order to pass this unit, a student must achieve at least 40% in the final examination. For subjects without a final exam, the 40% minimum requirement applies to the corresponding major assessment component specified by the lecturer. A student must also achieve an overall final mark of 50 or more. Any student not meeting these requirements may be given a maximum final mark of no more than 45 regardless of their average.

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

For more information see guide to grades.

Use of generative artificial intelligence (AI)

You can use generative AI tools for open assessments. Restrictions on AI use apply to secure, supervised assessments used to confirm if students have met specific learning outcomes.

Refer to the assessment table above to see if AI is allowed, for assessments in this unit and check Canvas for full instructions on assessment tasks and AI use.

If you use AI, you must always acknowledge it. Misusing AI may lead to a breach of the Academic Integrity Policy.

Visit the Current Students website for more information on AI in assessments, including details on how to acknowledge its use.

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 assessment in this unit unless an approved special consideration is granted. However, multiple submissions are allowed. The last submission BEFORE the deadline will be marked.

Academic integrity

The University expects students to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.

Our website provides information on academic integrity and the resources available to all students. This includes advice on how to avoid common breaches of academic integrity. Ensure that you have completed the Academic Honesty Education Module (AHEM) which is mandatory for all commencing coursework students

Penalties for serious breaches can significantly impact your studies and your career after graduation. It is important that you speak with your unit coordinator if you need help with completing assessments.

Visit the Current Students website for more information on AI in assessments, including details on how to acknowledge its use.

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.

Support for students

The Support for Students Policy 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. 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

Weekly schedule

WK	Topic	Learning activity
Week 01	Representations: bits, numbers, characters, insrructions. Operating systems: function, purpose.	Lecture and tutorial (4 hr)
Week 02	Main subcomponents of OS. Processes. Command line.	Lecture and tutorial (4 hr)
Week 03	Emulation and virtual machines.	Lecture and tutorial (4 hr)
Week 04	Kernel space, user space; Namespace and file system.	Lecture and tutorial (4 hr)
Week 05	Memory. Scheduling. Boot Sequence.	Lecture and tutorial (4 hr)
Week 06	Networks; Layering principle and protocols	Lecture and tutorial (4 hr)
Week 07	Internetworking: TCP/IP	Lecture and tutorial (4 hr)
Week 08	Domain Name Service; Application layer protocols	Lecture and tutorial (4 hr)
Week 09	Concepts of cloud computing	Lecture and tutorial (4 hr)
Week 10	Computer and network security.	Lecture and tutorial (4 hr)
Week 11	Introduction to data storage	Lecture and tutorial (4 hr)
Week 12	Introduction to distributed computing	Lecture and tutorial (4 hr)
Week 13	Where to next? Review of semester and exam	Lecture and tutorial (4 hr)

Attendance and class requirements

Course websites

Canvas and Ed are both used in this unit. The teaching staff will use them to communicate the unit's information to all students and make important announcements. They are considered part of the unit. Students are expected to regularly visit them to know these announcements and information concerning the format and schedule of the assessments. Canvas is a website that will be used to disseminate the online lecture recordings and to publish the results.

Attendance

A 2-hour lecture is held onsite. In addition, students must attend a 2-hour onsite tutorial / lab session every week, starting in week 1.

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.

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. manage their time and activities in a multi-week individual project
LO2. produce clear written report
LO3. extend their knowledge, acquire new knowledge, and connect to conceptual frameworks in operating systems and networks and the impact on application development, without explicit instruction
LO4. understand basic functions that an operating system performs, and know the main subcomponents of the OS
LO5. understand basic functions that networking performs, and know the most important layers/subcomponents in networking
LO6. use essential system tools to monitor OS and network status
LO7. understand additional concepts relevant for OS for server and for handhelds, including virtualisation and containers
LO8. demonstrate experience with a number of different operating systems
LO9. identify the interfaces at which users/applications can interact with the OS and the network, and identify where the OS function or network communication needs to be protected against unauthorized access
LO10. understand major ideas used in internal implementation of OS and networks, such as caching, process structures, memory mapping, layering, reliable/unreliable transport, multiplexing and packet switching
LO11. demonstrate awareness of some key algorithmic approaches that can be used in some subcomponents of OS and networking (eg routing, scheduling); also aware of alternative implementations in some cases, and of the tradeoffs involved
LO12. write basic application functionality to interact with the operating system and the network, e.g. by opening and closing files, writing to disk, and sending application-layer data to remote applications
LO13. demonstrate awareness of several major challenges that arise in distributed systems and mobile applications, e.g. failure tolerance and latency tolerance.

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.

Three main changes were made to this unit as a result of last year's Unit of Study Survey (USS): 1- No weekly homework due on the week an assignment is due. This results in fewer homework sets with slightly higher weights each. 2- Equal weight for both Assignment 1 and Assignment 2. 3. A third low-weight Assignment to practice the final exam. 4. Weekly quizzes to revise the lecture material.

Additional information

IMPORTANT: School policy relating to Academic Dishonesty and Plagiarism. In assessing a piece of submitted work, the School of Computer Science may reproduce it entirely, may provide a copy to another member of faculty, and/or to an external plagiarism checking service or in-house computer program and may also maintain a copy of the assignment for future checking purposes and/or allow an external service to do so.

Computer programming assignments may be checked by specialist code similarity detection software. The Faculty of Engineering currently uses the similarity report available in ED (edstem.org). This program works in a similar way to TurnItIn in that they check for similarity against a database of previously submitted assignments and code available on the internet, but they have added functionality to detect cases of similarity of holistic code structure in cases such as global search and replace of variable names, reordering of lines, changing of comment lines, and the use of white space.”

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

Early feedback task

Assessment summary

Assessment criteria

Use of generative artificial intelligence (AI)

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Support for students

Weekly schedule

Weekly schedule

Attendance and class requirements

Study commitment

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

INFO1112: Computing 1B OS and Network Platforms

Semester 2, 2025 [Normal day] - Camperdown/Darlington, Sydney

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Early feedback task

Assessment summary

Assessment criteria

Use of generative artificial intelligence (AI)

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Support for students

Weekly schedule

Weekly schedule

Attendance and class requirements

Study commitment

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