Syllabus


Course Goals

This course should develop students' sense of what really happens when software runs — and that this question can be answered at several levels of abstraction, including the hardware architecture level, the assembly level, the C programming level, and the Java programming level. The core around which the course is built is C, assembly, and low-level data representation, but this is connected to higher levels (roughly how basic Java could be implemented), lower levels (the general structure of a processor), and the role of the operating system (but not how the operating system is implemented).

For (computer science) students wanting to specialize at higher levels of abstraction, this could, in the extreme, be the only course they take that considers the “C level” and below. However, most will take a subset of , , , etc.

For students interested in hardware, embedded systems, computer engineering, computer architecture, etc., this course is the introductory course after which other courses will delve both deeper (into specific topics) and lower (into hardware implementation, circuit design, etc.). Of particular interest are , , , and .



Course Themes

The course has three principal themes:

  • Representation: How different data types (from simple integers to arrays of data structures) are represented in memory, how instructions are encoded, and how memory addresses (pointers) are generated and used to create complex structures.
  • Translation: How high-level languages are translated into the basic instructions embodied in process hardware with a particular focus on C and Java.
  • Control Flow: How computers organize the order of their computations, keep track of where they are in large programs, and provide the illusion of multiple processes executing in parallel.


Course Objectives

At the end of this course, students should be able to:

  • Describe the multi-step process by which a high-level program becomes a stream of instructions executed by a processor;
  • Describe the basic organization of the memory hierarchy and the effect of its parameters on system performance;
  • Trace the execution of assembly code (x86-64), map the assembly to high-level language constructs, and write simple pieces of assembly programs;
  • Write C code using pointers to create and manipulate complex data structures;
  • Write (or rewrite) code to be take advantage of the computer execution model to improve execution efficiency;
  • Debug small-ish C and assembly programs using GDB;
  • Explain the role of an operating system;
  • Describe fundamental differences between Java and C.


Course Syllabus

Approximate list of topics:

  • Memory and data representation
  • Number representation for integers and floats
  • Machine code and the C programming language
  • x86-64 assembly language
  • Procedures and stacks
  • Arrays and other data structures
  • Memory and caches
  • Operating system process model
  • Virtual memory
  • Memory allocation
  • Implementation of high-level languages (e.g., Java)

Note that even more important than the topics at various levels of abstraction is the connection between them: students should get an informal sense of how Java could be translated to C, C to assembly, and assembly to binary.



Course Components

The course consists of the following elements:

  • Pre-Lecture Reading: The main technical material will be introduced via interactive readings and check-in questions on the platform. These should be completed before engaging with lecture material.
  • Lectures: There will be 30 lectures (though 1 will cover section material). In-person attendance is highly encouraged, but lecture recordings and activities will be made available afterward.
  • Online Assignments (Homework): There are 23 online homework assignments, one roughly every lecture. These are intended to solidify the lecture concepts and are due at least two lectures later, though they are intended to be completed before the next lecture.
  • Programming Assignments (Labs): There are 6 total labs, due roughly every other week. All the undergraduate lab machines (and the CSE VM) will have access to the necessary tools. We will use these assignments to reinforce key concepts and will strive to have them be as practical as possible.
  • Reading: There will be corresponding optional readings from that correspond to lecture topics.
  • Exams: There will be a midterm and a final — see the for more information.

We will try to ensure that the workload is typical for a 4-credit course, namely, 9-12 hours per week outside of the lectures. If we do not succeed, please let us know in whichever way you feel the most comfortable (in-person, email, ) and explain which parts of the course are causing you to spend too much time non-productively.

We have structured the course so that spending a few hours per day will maximize your efficiency. You will work this way in the real world – you cannot cram a three-month design assignment into the last night – so you may as well work this way now. Plus, you will understand the material better. If you leave an assignment for the day before it is due you will not have time to ask questions when (not if) the software misbehaves.


Policies


Grading Policies

We will compute your course grade as follows:

  • Pre-Lecture Readings: 5%
  • Homework: 20%
  • Labs: 40%
  • Midterm: 16%
  • Final: 16%
  • Effort, Participation, and Altruism: 3%

The grading policies are designed to be relatively forgiving, so we expect a high grade distribution. We will use an approximate "straight-scale" grading scheme:

  • 97% → 4.0, 92% → 3.5+, 85% → 3.0+, 75% → 2.5+, 65% → 2.0+

EPA: Effort, Participation, and Altruism

You can earn "points" for each of the following:

  • Effort: Attending lecture, section, and office hours; keeping up with Ed Discussion.
  • Participation: Participating during lecture, including completing lecture questions, and interacting with TAs and other students; asking questions on Ed Discussion.
  • Altruism: Helping others in lecture, section, during office hours, and on Ed Discussion.

EPA scores are kept internal to the staff (i.e., not disclosed to students).


Lecture Polling

You will receive credit for voting on multiple choice questions in lecture. This quarter we will be using , which you should have open during lecture (whether live or recorded).

These questions are designed to give you a chance to check your understanding of the material by applying it on-the-spot, as well as an opportunity to interact with your classmates. These are intended to be low-pressure and lenient so the grading primarily reflects participation (i.e., your answer does not need to be correct). Earning ~80% of the possible points should get you full credit for lecture questions.


Extra Credit (Labs)

We will keep track of any extra credit items you complete on labs. You won't see these affecting your grades for individual labs, but they will be accumulated over the course and will be used to bump up borderline grades at the end of the quarter.

The bottom line is that these will likely have NO effect on your overall grade (and only a small amount if you are on a borderline). You want to be sure you have completed the non-extra credit portions of the lab in perfect form before attempting any extra credit. They are meant to be fun extensions to the assignments, so if you complete some extra credit it *may* positively impact your overall grade.



Assignment Policies

All assignment submission deadlines have an implied "and zero seconds" attached to them. This means that if your clock reads the deadline time (e.g., "11:59"), then your assignment is late! In addition, online submission can be fickle, so we highly recommend making partial submissions as you go and not waiting until the last (literal) minute to submit.

  • Pre-Lecture Readings have quiz questions and are graded on completion, so late submissions are NOT allowed. After submitting an answer, you are encouraged to revisit your work and submit again, though you are able to reveal the correct answer and solution if you are short on time. Readings are intended to be done before your lecture, but are due at 2:00 pm (30 min before the start of Lecture B).
  • Online assignments (homework) are autograded and late submissions are NOT allowed. You are allowed an unlimited number of attempts for each quiz and you will receive credit for every question that you answer correctly. Homework are due at 11:59 pm.
  • Programming assignments (labs) are submitted by uploading files to Gradescope assignments. Late lab submissions are subject to the late day policy described below. Note that you will sometimes need to submit the same file(s) to the separate extra credit assignments if you would like to have those graded. Labs are graded by a combination of grading scripts and TAs. Labs are due at 11:59 pm.
  • Exams are "take-home" and must be completed within the allotted window of time. See the schedule or the for dates. Exams are graded by the staff and will be handled via .

Late Day Policy (Labs)

You are allocated a total of 5 late day tokens for the entirety of the quarter to utilize on labs should the need arise.

  • A late day is defined as the 24 hour period after an assignment's due date: num_late_days = ceil(hours_late / 24).
    • An exception is made for weekends, which count as a single late day. That is, if an assignment is due at 11:59 pm on Friday, submitting before Sunday at 11:59 pm counts as using only ONE late day (submitting by 11:59 pm on Monday would count as using TWO late days).
  • All lab submissions will close two late days past the original due date.
  • There is no bonus for having leftover late days at the end of the quarter.

For each late day you use that exceeds the total late day tokens given to you, you will be penalized 20% of your score on one of the assignments that you submitted late. The penalties will be applied in a manner that maximizes your overall grade (i.e., minimizes your total penalties). No individual assignment will be penalized more than twice.


Solutions and Regrades

  • Pre-Lecture Reading: Solutions will be provided for most quiz questions once answered correctly or revealed.
  • Homework: Solutions will not be provided. Since you are allowed multiple attempts, make sure to go to office hours or talk to classmates if you feel stuck.
  • Labs: Solutions will not be provided. Most labs will include testing tools to allow you to evaluate whether or not your solution is likely working. Your lab grades will provide comments for any portion deemed incorrect.
  • Exams: Solutions will be posted on the after all students have taken the exam.

Learning from our mistakes is often one of the most memorable ways of learning and the staff is not immune from making them, too! If you have a question about a graded assignment or exam, please don't hesitate to ask a staff member about it during their office hours or via private post on Ed Discussion. If, after discussing your question, you feel that your work was misunderstood or otherwise should be looked at again to see if an appropriate grade was given, we ask that you submit an electronic regrade request via the interface, which will open and close automatically. Note that when an assignment is regraded, the entire work will be regraded. This means that while it is possible to regain some points, it is also possible to lose points.

  • Pre-Lecture Reading regrades: These are autograded, but if you believe there might be an error in our answers, please email the instructor or make a private post on Ed Discussion.
  • Homework regrades: These are autograded, but if you believe there might be an error in our answers, please email the instructor or make a private post on Ed Discussion.
  • Lab regrades: Make sure to include a short summary describing why your work should be looked at again.
  • Exam regrades: Submit separate regrade requests for each subquestion. Each regrade box is for only that particular part of the exam. Make sure you explain why you believe that your exam has been misgraded based on the provided solutions and Gradescope rubrics.


Face Covering

It is important for all of us to do our part to minimize the spread of COVID-19. An important part of working to keep our community safe is the University of Washington COVID-19 Face Covering Policy and requirements. This policy requires all members of the UW community to wear a face covering when in the classroom or indoors space, regardless of vaccination status. The UW encourages all students to take responsibility for following public health guidelines, being aware of COVID-19 information and steps for minimizing the spread of the virus. You can support the Husky Experience by wearing a mask and by getting vaccinated, if you haven’t already. Don't forget to attest to your vaccination status.

Eating and drinking will not be permitted in class. We are committed to providing a high-quality Husky Experience for every student and together we can keep our community healthy. Further information on COVID-19 practices and resources can be found at: https://www.washington.edu/coronavirus/



Academic Conduct

In general, we encourage collaboration, but there is a very fine line between collaboration and cheating. We can learn a lot from working with each other and it can make the course more fun, but we also want to ensure that every student can get the maximum benefit from the material this course has to offer. Keep in mind that the overall goal is for *YOU* to learn the material so you will be prepared for the exams and for job interviews etc. in the future. Cheating turns the assignments into an exercise that is a silly waste of both your time and ours; save us both by not doing it.

Permitted collaboration:

  • Pre-Lecture Reading: Collaboration and discussion is encouraged to help prepare you for the lecture.
  • Homework: Collaboration and discussion is encouraged (find a homework group!), but you are responsible for understanding the solutions on your own, as the problems are meant to solidify your grasp of the material, which is helpful for exams.
  • Labs: Outside of your (optional) partner, collaboration should be restricted to high-level discussion (i.e., ideas only). A good rule of thumb is that you should never show your own code while helping another student (viewing their code is highly discouraged, as it often leads to problematic situations).
  • Exams: Exams are taken individually and any attempt to use unpermitted materials or copy off of another student's exam will be heavily punished.

Cheating consists of sharing code or solutions to assignments by either copying, retyping, looking at, or supplying a copy of a file. Examples include:

  • Coaching a friend to arrive at a solution by simply following your instructions (i.e., no thinking involved). An example is helping a friend write a program line-by-line.
  • Copying code from a similar course at another university or using solutions/code on the web, including GitHub and Chegg.
  • Communicating your solution with another student via electronic or non-electronic means.

Cheating is a very serious offense. If you are caught cheating, you can expect a failing grade and initiation of a cheating case in the University system. Cheating is an insult to the instructor and course staff, to the school and program, and most importantly, to you and your fellow students. If you feel that you are having a problem with the material, or don't have time to finish an assignment, or have any number of other reasons to cheat, then talk with the instructor. Just don't cheat.

If you are in doubt about what might constitute cheating, send the instructor an email describing the situation and we will be happy to clarify it for you. For more information, you may consult the school's .



Disability Resources

The is a unit within the Division of Student Life and is dedicated to ensuring access and inclusion for all students with disabilities on the Seattle campus. They offer a wide range of services for students with disabilities that are individually designed and remove the need to reveal sensitive medical information to the course staff. If you have a medical need for extensions of exam times or assignment deadlines, these will only be granted through official documentation from DRS. Browse to to start the process as soon as possible to avoid delays.

You can refer to the university policies regarding for more information.



Religious Accommodations

Washington state law requires that UW develop a policy for accommodation of student absences or significant hardship due to reasons of faith or conscience, or for organized religious activities. The UW's policy, including more information about how to request an accommodation, is available at . Accommodations must be requested within the first two weeks of this course using the .



Extenuating Circumstances and Inclusiveness

We recognize that our students come from varied backgrounds and can have widely-varying circumstances. If you have any unforeseen or extenuating circumstance that arise during the course, please do not hesitate to contact the instructor in office hours, via email, or private Ed Discussion post to discuss your situation. The sooner we are made aware, the more easily these situations can be resolved. Extenuating circumstances include work-school balance, familial responsibilities, military duties, unexpected travel, or anything else beyond your control that may negatively impact your performance in the class.

Additionally, if at any point you are made to feel uncomfortable, disrespected, or excluded by a staff member or fellow student, please report the incident so that we may address the issue and maintain a supportive and inclusive learning environment. Should you feel uncomfortable bringing up an issue with a staff member directly, you may consider sending or contacting the .