Syllabus

Posted on November 24, 2023 · 12 minute read

Table of Contents

Course Description

In this course, we will dive deep into the mechanisms by which computer systems manage and distribute resources using the services of an operating system. You will learn how programs are turned into system processes and then are scheduled to run on the CPU. We will explore topics related to memory and file-system management as well as security and privacy from the system’s administrator point of view. Finally, in this class, you will have the opportunity to interact with a real-world, yet small-scale, operating system. You will implement several operating system features that will solidify the concepts that we discuss in class.

If you are wondering why you are required to take this class, please take a moment to read the unofficial syllabus where we try to convince you of the importance of knowing the concepts in this class.

Prerequisite Topics

At the start of this class, we assume that you are familiar with the C programming language and are well on your way to become an independent programmer. Officially, this means that you should have passed CSSE-132 and CSSE-220.

Learning Objectives

After completing this class, you should be able to:

  1. Leverage operating system services to create, manage, terminate, and schedule processes.
  2. Define the main memory abstraction and implement operating system features to achieve memory virtualization using paging.
  3. Describe different approaches to file-system organization and build a working system that can read, write, and manage files.
  4. Identify the need for synchronization in multi-threaded environments, and write code that properly uses synchronization primitives.
  5. Implement operating system features that satisfy a requirements specification using an appropriate programming language.

Textbook

  • Operating Systems: Three Easy Pieces, version 1.00, Remzi H. Arpaci-Dusseau and Andrea C. Apraci-Dusseau, August 2018.

Unless otherwise specified, all Chapters and Sections listed on the schedule refer to the above textbook and chapters.

Other great references

  • Modern Operating Systems, 4th Edition, Andrew S. Tanenbaum, Herbert Bos, Pearson Education, 2015.

  • Linux kernel development, Robert Love, Pearson Education, 2010.

  • Operating System Concepts, 10th Edition, Abraham Silberschatz, Greg Gagne, and Peter B. Galvin, Wiley, 2018.

Other References

  • C Programming Language, 2nd Edition, Brian W. Kernighan and Dennis M. Ritchie, Prentice Hall, 1988.

  • C: The Complete Reference, 4th Edition, Herbert Schildt, McGraw-Hill Osborne Media, 2000.

  • Advanced Programming in the UNIX Environment, 2nd Edition, W. Richard Stevens and Stephen A. Rago, Addison-Wesley Professional, 2008.

Electronic Course Materials

  • Electronic course materials, including the schedule, may be accessed directly at the course website.

  • All grades and assignment feedback will be posted on Gradescope.

  • Posting questions, discussions, and answers to questions asked are best done on the course’s Moodle forum.

Deadlines and Late Policy

The deadlines of all homeworks, labs, and project milestones are listed on the schedule page.

In general, you should plan ahead and submit assignments on time. This course has no ’late day’ policy and late assignments are generally worth 0 points unless you have made arrangements. This class is fast-paced, if you started delaying work, things will snowball very quickly, so plan ahead and start early.

However, we understand that situations out of control may arise. We handle all situations on a case-by-case basis. Here are some general guidelines:

  • You should make arrangements with your instructor ahead of time, minimum 24 hours before the assigned deadline.
  • The usual extension is 24 hours upon request or for extreme circumstances 48 hours
  • We keep track of extensions per student and if you seem to be overusing the privilege we will stop allowing extensions.
  • If the reason you are late is because you are having trouble completing the assignment (e.g. a bug you can’t fix or just difficulty understanding) get help from an instructor. Don’t assume that more time will fix the problem; plan to get help.

Special Arrangements

If circumstances have caused you to miss/fail several assignments OR if your current situation in OS seems overwhelming, you should contact your instructor right away. Sometimes it is possible to make up missed work for partial credit, these situations are always handled on a case-by-case basis.

The best chance of success is when these problems are addressed timely - but it never hurts to have a discussion, however unsalvageable the situation may feel. Please talk to your professor if you are having problems!

Homework Assignments/Labs

Homework assignments, including Labs, are listed on the class schedule. Each assignment includes instructions on obtaining the code and submitting it, please follow those instructions carefully, especially when it comes to what files you should be submitting; submitting object files and executables will cause all sorts of issues when grading. The instructions on which files to submit are there for a reason!

Assignments are split into two major types:

There are regular programming assignments, plus assorted quizzes and minor assignments (you can see the exact weight of everything in Moodle). These assignments are integral to your understanding of OS - missing any of them can make passing OS quite hard. All these assignments are done individually.

There are also challenge assignments. Challenge assignments generally involve trickier programming but explore more interesting topics. Despite the fact that they are harder, the challenge assignments are actually weighted less than regular assignments. You can pass the class without doing all challenge assignments, but your grade will be capped at a C, leaving you little room to make mistakes on labs and exams. BUT it’s our hope everyone will attempt at least some of the challenge assignments, and those looking for an A will need to complete all of them. Challenge assignments can be done in groups of 2, or individually.

Exams

There will be 2 skill exams and a final exam. Please make note of the following:

  • You must earn a passing (60%) average on the exams to pass the course.
  • You must earn at least a C (70%) average on the exams to earn a C or better in the course.

Grading

Item Weight
Assignments/Labs 40%
Challenge Assignments 15%
Project 10%
Exams 35%

I generally follow the registrar’s interpretation of letter grades, which you can find here under the grades description section.

Handling Grading Issues

Thankfully, Teaching Assistants will be helping us grade most of the homework in this class. On the schedule page, you should be able to see who will be grading a particular assignment. When you have a grading issue, please contact the grading TA first, particularly for issues like:

  • The code you submitted works on your computer but not the TA’s.
  • The TA didn’t notice but you actually did do the thing requested, it was just in a different place etc.
  • You submitted the wrong files.

If you talk to the grading TA and you disagree with their analysis of your code or you feel the grading standards were unfair (or unfairly applied) please contact your instructor. We want to help you but everything goes smoother if logistical issues come to the TAs first.

Collaboration, Cheating and Professional Behavior

The sections below provide specifics on academic misconduct and its consequences. Please understand that these policies are rooted in the fact that we are here to teach, and you are here to learn!

Plagiarism and General Misconduct

If you plagiarize any part of your work or take part in any form of academic misconduct (including hindering the work of other students), you will automatically receive a grade of F for the class and the incident will be reported for further disciplinary action.

Self-plagiarism

Students who turn in work derived from a past attempt at the course shall receive an F in the course.

Self-plagiarism is copying and reusing all or some of your previous work for another course attempt. There are several issues with reusing your own work, including:

1. It probably wasn't of high quality (since you're here retaking the
   course).
2. It gives you a time advantage over other students.
3. You are not learning the material by resubmitting existing work.

While all of these are significant issues, the last one is our biggest concern. If you are retaking the class, you should be redoing the work, as the practice helps reinforce course concepts.

Self-plagiarism will be treated as any other form of academic misconduct.

Generative Artificial Intelligence

Work for this course must be your own! This means that you wrote or designed it on your own, without the use of generative AI platforms. Work wholly or partially created through generative AI will be treated as any other form of academic misconduct.

What is considered generative AI?

The term generative AI is not necessarily restricted to large language models accessible through online platforms, such as ChatGPT or Bard. Plugins that use generative AI to complete code fragments (mainly GitHub Copilot) also fall under this policy and will be treated similarly. Using any plugin in your IDE that interacts with these generative AI models will be considered as academic misconduct.

On exams, you will be asked to refrain from using an IDE, and are restricted to using a terminal-based editor on a remote server. It is therefore in your best interest to practice using that platform on the lab assignments, in preparation for the exam. In addition, using any resources not specifically allowed during the exam, such as communication platforms (MS Teams, Slack, Discord), will be considered academic misconduct. At the start of the exam, you will be asked to quit all these platforms and turn off all notifications they might generate. Failure to do so will be reported as a case of academic misconduct.

Why no generative AI?

Basically, because we want you to learn how to do it. Yes, generative AI will be a part of our future, but it may not always be available to you, and if you do have access, you need to understand if the work you receive from it is any good. In the first case, generative AI platforms can store and repeat what they’re given. Imagine working with confidential company information or in classified government work? You cannot feed it the information on what you want, because that information will become part of its network. Beyond that, you cannot simply assume that an AI did good work. Even if you end up in a job that is AI-assisted, a human still needs to be able to evaluate if the work was done properly or not, you won’t be able to do that unless you have experience doing the work yourself.

Collaboration

We generally welcome and encourage discussions on homework and lab assignments. Such discussions about ideas are not considered cheating, and can be very beneficial for your learning experience. However, the exchange of code or written answers is cheating!

In such discussions of ideas, you should distinguish between helping or hurting yourself and the other student(s). In brief, you can help each other by teaching yourselves, but you can hurt each other by giving each other answers, such as a key idea needed to work through a problem. The same applies to tutoring and getting help from the instructor.

If you use reference materials (other the course texts and resources) to solve a problem, please cite the references material. Similarly, if you discuss a solution with another student, give credit where credit is due by making a note such as “the following idea was developed jointly with Alyssia P. Hacker”, or “the following idea is due to Ben Bittwiddle”. You cannot be charged with plagiarism if you cite in this way. However, copying and reusing code, even with such a citation, is still considered cheating. Cooperation refers to the exchange of ideas, not code or written answers. Collaboration refers to helping one another understand course material, not providing shortcuts to completing course work.

Summary

The instructors take plagiarism seriously. Students caught plagiarizing, or cheating in any way, will be reported to the dean of students and will receive an automatic F in the class.

A statement on mental health

We know that as students, you are dealing with a lot of stress, often a lack of sleep, and sometimes social isolation. It is easy to neglect your mental (and physical) health and lose yourself in the vortex of pressure. Spoken from experience, it is important for you to make time for yourself, both mentally and physically. Therefore, if at any point during the quarter, you feel that you are in need of help, please reach out to the office of health services or the student counseling center. Also, if you feel comfortable, you can reach out to me so I can help you devise a plan to tackle your coursework for CSSE 332.

Miscellaneous

Syllabus changes

Please note that the syllabus is a living document. We reserve the right to change the syllabus at any time, but you will notified of any changes.

Attendance policy

It is in your best interest to attend all class sessions, as we will often be doing coding activities that will feed directly into your homework or lab assignments.

Therefore, up to two unexcused absences are allowed. Any additional unexcused absence may result in you receiving a failing grade for the course. You will be responsible for making up any missed work during those unexcused absences.

Illness

We understand illnesses may arise and you will need to take some time to recover, resulting in missing class sessions. In such case, please do inform your instructor as soon as possible about your situation; the details of your situation that you wish to share are totally up to you. To protect your classmates and yourself, please do not come to class ill, especially if it is COVID-related.

Laptop policy

You may need to use your laptops during a portion of class periods. Please be sure to bring your laptop and a power brick to class.

During class discussion, please do not use your laptops. Studies have found that using your device during class time (non work time) hinders your learning as well as that of your classmates. Class time is not the time to catch up on anime or to make that big push on league of legends!

However, if you typically use your laptop for note taking, please talk with your instructor so they can make an exception.

Acknowledgments

This syllabus was last modified by Mohammad Noureddine on Fri 24 Nov 2023. It is built on the contribution of various instructors, including Mike Hewner, Lixing Song, and Mark Hays.