Operating Systems

About

Catalog Description

Aim

The aim of this course is to introduce students to operating systems concepts.

Objectives

At the end of this course the student should be able to:

1. describe the purpose and functions of an operating system;
2. design and implement programs to perform simple operating system tasks; and
3. evaluate the performance of different operating system algorithms.

Topics (based on ACM's 2023 Curriculum Guidelines)

1. OS/Overview of Operating Systems
2. OS/Operating System Principles
3. OS/Concurrency
4. OS/Scheduling and Dispatch
5. OS/Memory Management
6. OS/Security and Protection
7. OS/Virtual Machines
8. OS/Device Management
9. OS/File Systems
10. OS/Real Time and Embedded Systems
11. OS/Fault Tolerance
12. OS/System Performance and Evaluation
13. SF/Cross-Layer Communications
14. SF/Resource Allocation and Scheduling
15. SF/Virtualization and Isolation

Assessments and Grading(may be adjusted)

(A) Two Lecture Exams	40%
(B) Lecture Quizzes/Homeworks	10%
(C) ICS-OS Project (individual)	10%
(D) Laboratory	40%
(E) Final	A+B+C+D=100%

Passing grade is 55%. No grade of 4.0 will be given. Grading scale is shown below.

0.00	54.99	5.0
55.00	59.99	3.0
60.00	64.99	2.75
65.00	69.99	2.5
70.00	74.99	2.25
75.00	79.99	2.0
80.00	84.99	1.75
85.00	89.99	1.5
90.00	94.99	1.25
95.00	100	1.0

Policies

Attendance Policy

The University Policy on Attendance will apply.

Collaboration Policy

All lab activities will be done individually. Discussions are allowed but there should be no sharing/direct copying of code.

Academic Integrity and Generative AI Use

• Properly acknowledge help received by indicating your sources in your submissions.
• No looking at solutions/programs from previous years.
• No sharing of code with other students. Be ready to explain your code.
• By default you are not allowed to used AI tools during lab classes. You may use AI tools in this course only when allowed and never to replace your own work. AI can help with brainstorming, explanations, or debugging (if permitted), but you must verify results, credit the tool, and explain your work yourself. Do not use AI to generate complete solutions for graded work, plagiarize, or submit misleading content. Misuse will be treated as academic misconduct. Use AI to learn, not to cheat.

Communication and LMS

We will use Google Classroom, GitHub Classroom, and Slack.