CMSI 387 - Operating Systems
Professor Andrew Forney • Andrew.Forney[at]lmu.edu • Spring 2018 • DOO 219 • 2:40 pm - 4:10 pm
CMSI 387 is a 3-Unit course providing the introductory theory behind, and practice implementing, a selection of core concepts in operating system design. Though an OS is a program itself, its responsibilities include running all other programs, managing memory, and a host of other important tasks that will be covered throughout the course.
Learning Outcomes
By the course's end, students will:
become "agile" at navigating and manipulating a file system through bash commands, scripting, and a variety of other command-line tools.
understand the fundamental roles that OS's play in computer organization, including management of booting, I/O, memory, processes, the file system, and security.
possess experience comparing different real-world OS's and gain greater familiarity with flavors of Linux.
gain practice implementing core OS concepts in C as well as navigating common challenges like deadlock.
Prerequisites
Warning: before taking this course, it is assumed that you have a sufficient knowledge of the basics of the C programming language, and computer systems organization (topics of CMSI 284).
This class uses C for its concrete examples, homework, and exams. We will not spend much class time reviewing C fundamentals, though you are welcome to ask for clarification at any point.
If you require additional practice, you may learn through any number of online tutorials.
Texts
We will be using one textbook for the course, which will primarily cover the theoretical material: Operating System Concepts (8th or 9th ed.) by Silberschatz, Galvin, and Gagne.. Although this specific text is not mandatory for the course, it contains all concepts that we will be covering in great detail, and your exams will expect that you understand these concepts.
Additionally, I will provide abbreviated course notes for our lectures on my course page (see Notes tab)
Resources will be provided throughout the course detailing any additional topics that are not sufficiently contained in the above text. These resources will be free and publicly available.
Lecture Attendance
Although not mandatory, lecture attendance is strongly advised since you'll otherwise miss out on all of our inside-jokes. Less importantly, you'll be missing out on lecture content that will not be posted online, classwork (see below), and hints for homework and exams. If you miss a lecture, the important points will be sketched in our course notes, though may be missing lecture-exclusive information (see Note tab on course page).
Lectures are participatory in nature, often with exercises and group-work to facilitate learning. Laptops are discouraged for note-taking, but encouraged for working on in-class problems.
Workload Expectations
As this is a 3-Unit class, it is expected that you will be allocating an average of 6 hours per week working on course assignments, reading, and studying. Some weeks will have less material to keep you busy, and others more, but be aware that this is a work-intensive course that may require you to spend a lot of time programming!
Office Hours
Although you're always free to email me, I'll host some in-person office hours at the following times:
TR 4:30 - 6:30pm, DOO 201A
W 2:00 - 4:00pm, DOO 201A
On other days, you'll find me in the Keck Lab or my office (DOO 201A). If my door's open, stop by for any homework questions, lecture clarifications, or chat!
Tentative Schedule of Topics
The following constitutes the tentative schedule for topics to be covered in the course. This is largely an approximation for what we will cover each lecture, and is subject to change. For each topic, the relevant chapter of the textbook is also given, however, you are only required to understand the sections of each chapter that correlate with the material in the course notes -- the rest are for your curiosity and edification!
| Item | Date | Topic | Text Chapters |
|---|---|---|---|
| Lecture 1T | 1 / 9 | ||
| Lecture 1R | 1 / 11 | ||
| Lecture 2T | 1 / 16 | ||
| Lecture 2R | 1 / 18 | ||
| Lecture 3T | 1 / 23 | ||
| Lecture 3R | 1 / 25 | ||
| Lecture 4T | 1 / 30 | ||
| Lecture 4R | 2 / 1 | ||
| Lecture 5T | 2 / 6 | ||
| Lecture 5R | 2 / 8 | ||
| Lecture 6T | 2 / 13 | ||
| Lecture 6R | 2 / 15 | ||
| Lecture 7T | 2 / 20 | ||
| Lecture 7R | 2 / 22 | ||
| Lecture 8T | 2 / 27 | ||
| Lecture 8R | 3 / 1 | ||
| Holiday | 3 / 6 | ||
| Holiday | 3 / 8 | ||
| Lecture 9T | 3 / 13 | ||
| Lecture 9R | 3 / 15 | ||
| Lecture 10T | 3 / 20 | ||
| Lecture 10R | 3 / 22 | ||
| Lecture 11T | 3 / 27 | ||
| Lecture 11R | 3 / 29 | ||
| Lecture 12T | 4 / 3 | ||
| Lecture 12R | 4 / 5 | ||
| Lecture 13T | 4 / 10 | ||
| Lecture 13R | 4 / 12 | ||
| Lecture 14T | 4 / 17 | ||
| Lecture 14R | 4 / 19 | ||
| Lecture 15T | 4 / 24 | ||
| Lecture 15R | 4 / 26 | ||
| Final | 5 / 1 2:00 pm |
Assignments & Grading
Grade Decomposition
Grades will be assigned based on the following weighted coursework:
[20%] Classwork: Small classwork assignments will be given throughout each week, with in-class time allocated for their completion. Though you will have the opportunity to finish these in groups and with my assistance during class, you are not required to attend lectures, and so may submit these electronically by their listed due dates. Your lowest classwork grade will be dropped (even if you skipped it entirely).
[40%] Homework: Larger assignments with heavy coding required. Programming style and comments are graded as well. All homework assignments are weighted equally. Expect assignments once every ~2.5 weeks.
[40%] Exams: There will be 3 exams every ~5 weeks throughout the semester (including the final). Your best 2 exam scores will constitute 80% of the exam grade, with your worst score constituting the remaining 20%. For example, if your 3 exam scores were 70, 80, and 90, then your weighted exam score for the course will be 82 (= 70*0.2 + 80*0.4 + 90*0.4)
Final Grades
Final letter grades are given based on the university scale of grade percentages:
A: 93 - 100
A-: 90 - 92
B+: 86 - 89
B: 83 - 85
B-: 80 - 82
C+: 76 - 79
C: 73 - 75
C-: 70 - 72
D: 65 - 69
F: 64 and below
Fractional grade percentages at 0.5 or over will be rounded up, so an 89.5% will be considered a 90% (A-), but an 89.4% will be considered an 89% (B+) on the above scale.
That said, these are only the guaranteed grade assignments: if your "final" grade is an 82%, you are guaranteed a B- or better, but you might still get an A if 82% is the top score.
Extra Credit
Extra credit opportunities will be sporadically available during lectures / exams; if you are present and can hand in an attempt at the extra credit opportunities, you will receive bonus points!
If you receive all extra credit opportunities, you can gain a maximum +2% on your final grade. These bonuses are applied post-curve, so no student will be punished for not attending lectures relative to their peers.
Submission Standards
Each of your submitted homeworks and projects are subject to the following constraints:
Assignment posting: all assignments (classwork, homework, or otherwise) will be announced in class and posted on this site with due dates. You are responsible for checking this site's Announcements for any updates to assignments and their associated deadlines.
Late Policy: assignments are due at exactly the time indicated by the method specified. Assignments that are late by anywhere from 0 - 24 hours will only receive 80% of the points that they would have otherwise earned. Assignments that are late by 24+ hours receive a 0. There are no exceptions to this rule.
Individual Work: students are encouraged to talk and think about problems in groups, but each submission should be their own, containing no code that has been copy-pasted from another student. We take plagiarism very seriously, and each submission will be run through a similarity-checking mechanism to ensure fairness. Code or homework which we believe to be shared innapropriately between students is subject to severe disciplinary action. (not that you would, just sayin')
Style: assignments which are sloppily submitted without proper formatting, style, and comments are subject to penalties. As this is an upper-division computer science class, you should be intimately familiar with these stylistic requirements.
Resources
Tips for Success in this Class
Here are a few tips for succeeding in this class (and college, in general); they're not meant to sound patronizing, but rather, are simply pearls of wisdom to hand down from someone who has recently trodden your path!
Ask questions: if there is one piece of advice I can impart unto you, it's to ask questions when you have them. Chances are good that if you have a question, someone else has the same one, you won't be left behind wondering about something that was covered minutes ago (and which future material might employ), and I promise not to judge you for whatever you ask (well, not too hard at least). At the very least, if you have a question, write it down and then ask it after class. The heart of academic inquiry is just that: inquiry!
Fear not the specter of error: in college classes, there tends to be a crippling aversion to being wrong, especially publicly! I'm here to tell you that there is no better time to be wrong than in class, particularly in one as interactive as ours. There are a variety of silver-linings to being wrong: you won't forget what you were wrong about (one fewer thing to cram for later), it's better to learn from being wrong when it doesn't matter (i.e., in discussion) than when it does (i.e., on a test or during an interview), and I will respect you for your courage. There is only one circumstance in which you should fear error: when you fail to learn from it (at which point, see tip above for remedy).
Indulge your curiosity: and no, that's not some tagline stolen from a Vegas day-spa (actually, it might be, don't quote me on that), but the wisdom is sound... in class, we will cover a variety of topics with accompanying exercises that highlight the main take-away messages of the lesson, but that does not mean that your learning should stop there. Indeed, computer science is one of those beautiful disciplines wherein experimentation and exploration are so trivially entertained. Curious about what would happen if you changed the value of a variable? Do it! Curious about what other methods exist for certain data types? Google them! There is no reason why your learning should be constrained to what I (strategically) offer you; we have only limited time in class, and I'll prioritize the most important topics, but your interests can spread their own wings. Go forth and explore!
University Resources
Here are some LMU links for University Resources that might be of interest:
Academic Degree Requirements and Policies: Pay particular attention to honor code and process.
Computer Science Department (hey, who's that handsome guy on the left?)