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Unit outline_

INFO1112: Computing 1B OS and Network Platforms

Semester 2, 2024 [Normal day] - Camperdown/Darlington, Sydney

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 Hazem El-Alfy, hazem.elalfy@sydney.edu.au
Lecturer(s) Hazem El-Alfy, hazem.elalfy@sydney.edu.au
Tutor(s) David Shi, hongyi.shi@sydney.edu.au
Chris Polak, christopher.polak@sydney.edu.au
The census date for this unit availability is 2 September 2024
Type Description Weight Due Length
Supervised exam
? 
hurdle task
Final Exam
Final Exam
40% Formal exam period 2 hours
Outcomes assessed: LO3 LO6 LO12 LO4 LO5 LO7 LO10 LO11 LO13
Small continuous assessment Homework sets
Homework due in weeks 4, 7, 9
15% Multiple weeks 1 week
Outcomes assessed: LO4 LO13 LO12 LO11 LO10 LO9 LO8 LO7 LO6 LO5
Small continuous assessment Homework 1
#earlyfeedbacktask. Testing your Unix commands knowledge so far.
5% Week 03
Due date: 16 Aug 2024 at 23:59

Closing date: 16 Aug 2024
1 week
Outcomes assessed: LO3 LO4
Assignment Assignment 1
Programming task - introductory Unix
20% Week 05
Due date: 01 Sep 2024 at 23:59
4 weeks
Outcomes assessed: LO1 LO2 LO3 LO4
Assignment Assignment 2
Programming task - networking concepts
20% Week 11
Due date: 20 Oct 2024 at 23:59
4 weeks
Outcomes assessed: LO1 LO6 LO12 LO5 LO9
hurdle task = hurdle 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 due weeks 3, 4, 7 and 9.
  • Homework 1, due in week 3, is part of the Early Feedback Task.
  • Assignments due weeks 5, 11.
  • Final Exam (pen and paper) during the examination period.

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

Special consideration:
Approved special consideration will be given those outcomes:

  • Homework: Mark adjustment. No simple extension for homework.
  • Assignments: Extension of time. Assignments are eligible for simple extension. Mark adjustment cannot be granted for assignments.

Conditions for passing this unit:

  1. At least 50% of the total mark.
  2. 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.

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 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.

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 Representations: bits, numbers, characters, insrructions. Operating systems: function, purpose. Lecture and tutorial (4 hr) LO4
Week 02 Main subcomponents of OS. Processes. Command line. Lecture and tutorial (4 hr) LO3 LO4
Week 03 Kernel space, user space; Namespace and file system. Lecture and tutorial (4 hr) LO3 LO4 LO6
Week 04 Memory. Scheduling. Boot Sequence. Lecture and tutorial (4 hr) LO3 LO4 LO6
Week 05 Emulation and virtual machines. Lecture and tutorial (4 hr) LO3 LO4 LO6 LO7
Week 06 Networks; Layering principle and protocols Lecture and tutorial (4 hr) LO3 LO4 LO5 LO6
Week 07 Internetworking: TCP/IP Lecture and tutorial (4 hr) LO3 LO4 LO5 LO6 LO9 LO10
Week 08 Domain Name Service; Application layer protocols Lecture and tutorial (4 hr) LO3 LO5 LO6 LO7 LO9 LO10
Week 09 Computer and network security. Lecture and tutorial (4 hr) LO3 LO4 LO6 LO9
Week 10 Concepts of cloud computing Lecture and tutorial (4 hr) LO3 LO7 LO8
Week 11 Social network analysis Lecture and tutorial (4 hr) LO3 LO9 LO11 LO12
Week 12 Micro-services and internet based APIs Lecture and tutorial (4 hr) LO9 LO10 LO11 LO12 LO13
Week 13 Where to next? Review of semester and exam Lecture and tutorial (4 hr) LO3 LO4 LO5 LO6 LO7 LO12 LO13

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

The lecture is held remotely. 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 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. 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
GQ1 GQ2 GQ3 GQ4 GQ5 GQ6 GQ7 GQ8 GQ9

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- Outdated contents of a lecture were changed to a more recent topic.

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.