Syllabus & Course Policies

Overview

The first few CS courses are an introduction to computer science, with particular emphasis on software and on machines from a programmer's point of view.

1. CS 110 focuses on learning how to program for beginners.
2. CS 111 concentrates on the idea of abstraction, allowing the programmer to think in terms appropriate to the problem rather than in low-level operations dictated by the computer hardware.
3. CS 235 introduces more data structures and algorithms and the C++ programming language.
4. CS 224 focuses on machines and how they execute programs using the C programming language.

In CS 111, we are interested in teaching you about programming, not about how to use one particular programming language. We consider a series of techniques for controlling program complexity, such as functional programming, data abstraction, and object-oriented programming.

CS 111 primarily uses the Python 3 programming language. Python is a popular language in both industry and academia. It is also particularly well-suited to the task of exploring the topics taught in this course. It is an open-source language developed by a large volunteer community that prides itself on the diversity of its contributors. We will also use other languages in the latter half of the course.

Mastery of a particular programming language is a very useful side effect of CS 111. However, our goal is not to dictate what language you use in your future endeavors. Instead, our hope is that once you have learned the concepts involved in programming, you will find that picking up a new programming language is but a few days' work.

A complete list of lecture topics, readings, and assignments appears in the daily schedule.

Course Origin

We borrowed and adapted an initial version of this course from UC Berkeley’s CS61a course. UC Berkeley is one of the top CS programs in the world and their instructors and staff have put in a lot of time over the years creating CS61A. We appreciate their willingness to share their resources—course materials, assignments, etc.—with us. Special thanks to John DeNero, Pamela Fox, and Vanshaj Singhania.

After teaching that course for a year, we decided it wasn’t quite meeting the needs of our students in our program here at BYU. We’ve been redesigning it since the end of the Winter 2023 Semester. We piloted the new version of the course during the Summer term and have incorporated lessons learned from that term and from the following Fall semester. Some of the assignments are still under development. Bear with us as we make changes and adapt.

Prerequisites

Though there are no enforced programming-related prerequisites for CS 111, we strongly recommend prior Computer Science coursework or other exposure to programming equivalent to CS 110 or a score of 3 or above on the AP Computer Science A exam. We discourage students from taking the course without any prior programming experience, because they typically must work substantially harder to master the material. If you have limited prior experience and you find it challenging to complete all of the required coursework in the first week, strongly consider taking CS 110 first. You'll likely have a better experience taking CS 111 later, and you won't fall behind in any meaningful way by taking a preparatory class first.

Preparatory Classes

To build programming experience before taking CS 111, we recommend that you first take a course that introduces you to programming. The most appropriate class within the CS department is CS 110, described below, but you may also find other classes at BYU give you the necessary programming exposure. Feel free to contact course staff if you are not sure what's best.

CS 110

CS 110: How to Program is an introductory computer science course taught in Python. It focuses on learning how to program and developing core coding skills, whereas CS 111 focuses on higher-level coding concepts including abstraction, complexity, object-oriented programming, and the structure and interpretation of computer programs. CS 110 is the recommended course for CS majors and minors with little to no previous programming experience.

BIO 165

BIO 165: Introduction to Bioinformatics is an introduction to Bioinformatics designed for students in Biology or Bioinformatics. It teaches students to program in Python, but covers a much smaller subset of the language than CS 110. Most of the course focuses on programming to manipulate biological data stored in diverse file formats. Taking BIO 165 before CS 111 is a good way to gain prior programming experience, but taking CS 110 is a better way.

Course Format

The course includes many events and opportunities for learning: lectures, labs, open TA lab, office hours, and more. Everyone learns differently, so not all of these events are required. However, it is recommended that you try everything out to figure out what combination of these events works best for you.

Lecture

There are three 50-minute or two 75-minute lectures per week depending on your section during Fall and Winter Semesters. Lectures are tightly coordinated with Lab sections. Please attend each lecture the day it is given to better prepare for your lab section.

Lab Section

Each lab section meets twice each week during Fall and Winter Semesters. These sections are run by an amazing group of teaching assistants who have been carefully selected for their ability, enthusiasm, and dedication to learning. Getting to know your TA is an excellent way to succeed in this course.

Open TA Lab

In the open TA lab, you can ask questions about the material, receive guidance on assignments, and work with peers and course staff in a small group setting. See the lab hours and come by in-person or via Discord; no appointments are needed.

Assignments

Each week, there will be problems assigned for you to work on, most of which will involve writing and analyzing programs. These assignments come in three categories: lab exercises, homework assignments, and projects.

Labs

Labs will focus on practice of lecture topics in a “safe” environment. Lab assignments typically involve a number of small-group (2-4 people) programming tasks. Your programming partners may be mixed up each session to give you experience working with a variety of other people.

In labs, learning comes from practice and trial and error. Don’t be afraid to make mistakes and fail in lab. Mistakes are expected and even encouraged. In the words of Miss Frizzle, in the labs we expect you to “Take chances, make mistakes, and get messy!” Try code, see what works and what doesn’t, and discuss it with your peers (including the TAs). If you are attending and participating, you will have enough time to eventually get everything working with the help of your TAs and peers.

We strongly encourage attendance in the lab sections. Your learning experience will be much better if you attend, plus code written in lab will nearly always be used in future homeworks and projects. However, attendance (and enrollment) is ultimately optional. Whether or not you attend lab, to get credit for the lab assignments (15% of your total grade) you must complete them and submit them to the auto-grader. Your score will be based on how well you complete the assignment.

Homework

Homework assignments let you apply the concepts learned in lecture and lab to more challenging problems. Many of the homework assignments are designed to help you develop code for the next project and often build on materials practiced and developed in your lab sessions.

Projects

Projects are larger assignments intended to combine ideas from the course in interesting ways.

You are allowed and encouraged to pair program with a partner. Make sure to alternate roles so that both of you understand the complete results. We recommend finding a partner in your section, but course staff will also help with partner matching at various points in the semester. It is your responsibility to contact and collaborate with your partner. You may also work alone on all projects, although partners are recommended.

Exams

There will be three exams in Spring 2024:

• Midterm 1 will open Thursday, Oct 10 and will close Monday, Oct 14. There will be a $5 late fee if you take it on Monday in the testing center.
• Midterm 2 will open Thursday, Nov 14 and will close Monday, Nov 18. There will be a $5 late fee if you take it on Monday in the testing center.
• The Final exam will be available during the whole duration of Finals (Fri, Dec 13 - Wed, Dec 18).

Exams will be taken on Canvas.

UAC

We will provide appropriate accommodations to all students enrolled in the University Accommodations Center (UAC). To ensure that you receive the appropriate accommodations, make sure to send us your letter as soon as you receive it, confirming your status and accommodations. Please email all UAC letters to cs111headta@gmail.com and to your instructor.

Privacy

All UAC-related materials for this course are kept separate from the rest of the course materials, and they are visible only to instructors and selected staff.

For any UAC related communications, we recommend that you reach out to your instructor directly.

If you believe your accommodations may affect the TA who is teaching your section, and would like to inform that TA, you may wish to inform the instructor, who can inform your section TA on your behalf.

Extensions

If you need to request an extension, for UAC reasons or otherwise, please direct message (DM) your section leader TA via Discord (see Contact) as far in advance as possible, and certainly before the due date and time. Your request will be processed as quickly as possible. If you have a UAC accommodation for assignment extensions, requests will be approved as long as they are made in good faith. Longer extensions will be approved on a case-by-case basis. Also see the Late Policy section below.

Resources

Textbook

The optional online textbook for the course is Composing Programs, which was created specifically for the prior Berkeley version of this course, based on the classic textbook Structure and Interpretation of Computer Programs. Readings in these textbooks can provide additional information that will be helpful in understanding the lecture materials.

Grading

Your course grade is computed using a weighted category system. The weights of the various parts of the course are as follows:

• Labs – 15%
• Homework – 15%
• Projects – 25%
• Midterm 1 – 20%
• Final exam- 25%

This table shows the letter grade thresholds.

There is no curve; your grade will depend only on how well you do, and not on how well everyone else does. These thresholds will not be adjusted based on student performance. You could all get A's. You could all get D's.

These are the exact thresholds that will be used at the end of the course to assign grades.

Incomplete grades will be granted only for medical or personal emergencies that cause you to miss the final or last part of the course, only for students who have completed the majority of the coursework, and only if work up to the point of the emergency has been satisfactory.

Your lowest homework score will be dropped.

Each lab that you complete is worth 20 points. Your lowest two scores will be dropped.

For Computer Science Majors: please note that in order to fulfill the requirement for this course, you must pass with a C- or higher.

Late Policy

Please do all assignments by their due date. If you have extenuating circumstances and need to hand in something late, note that we can still give you full points, but not more time. Please work ahead instead of behind!

Getting behind in spring is very challenging. There are half as many nights and half as many weekends and still the same amount of work.

Due dates for each assignment are posted on the course website, on Canvas, and on Gradescope. We highly recommend you follow these due dates as closely as possible to prevent falling behind in the course. Keep in mind that future assignments nearly always build off of previous assignments. As such, don't expect that you'll be able to easily skip assignments and still keep up with concepts learned in lectures and labs.

Citizenship

For exceptionally rude or disrespectful behavior toward the course staff or other students, your final grade will be lowered by up to a full letter grade (e.g., from an A- to a B-) at the discretion of the course instructors. You don't need to be concerned about this policy if you treat others with even a bare minimum of respect and consideration and do not engage in behavior that is actively harmful to others.

Learning Cooperatively

With the obvious exception of exams, we encourage you to discuss course activities with your friends and classmates as you are working on them. You will learn more in this class if you work with others than if you do not. Ask questions, answer questions, and share ideas liberally.

Learning cooperatively is different from sharing answers. You shouldn't be showing your code to other students or looking at others' code, except:

• During lab, you can share all you want as long as you're all learning.
• For a project that allows partners, you can share anything with your partner.
• If you've finished a problem already, you can look at others' code to help them finish.
• Sharing is not allowed on Homework assignments; they should be completed and submitted individually.

If you are helping another student, don't just tell them the answer; they will learn very little and run into trouble on exams. Instead, try to guide them toward discovering the solution on their own. Problem solving practice is the key to progress in computer science.

If you're working collaboratively, keep your project partner informed. If some medical or personal emergency takes you away from the course for an extended period, or if you decide to drop the course for any reason, please don't just disappear silently! You should inform your project partner, so that nobody is depending on you to do something you can't finish.

Academic Honesty

Any students caught collaborating on exams will receive an E (failing grade) in the course. Please don't be one of these students.

Reading others' homework or project solution to a problem before you solve that problem on your own will incur large point penalties. You are free to discuss the problems with others beforehand, but you must write your own solutions. The exception to this rule is that you may share code with your project partner.

If you are unsure if what you are doing constitutes academic misconduct, please clarify with the instructor or contact course staff. The following is a list of things you should NOT do. This list is not exhaustive, but covers most of the big offenses:

• Do not copy code from any student who is not your partner.
• Do not allow any student other than your partner to copy code from you.
• Do not copy solutions from any online sources, such as Stack Overflow, Pastebin, and public repositories on GitHub.
• Do not use AI-assisted autocompletion (such as GitHub Copilot or ChatGPT) to complete assignments.
• Do not post your solutions publicly during or after the semester.

In summary, we expect you to hand in your own work, take your own tests, and complete projects with code written only by you and your partner. The assignments and evaluations are structured to help you learn, which is why you are here.

Rather than copying someone else's work, ask for help. You are not alone in this course! The entire staff is here to help you succeed. If you invest the time to learn the material and complete the projects, you won't need to copy any answers.

A Parting Thought

Grades and penalties aren't the purpose of this course. We really just want you to learn. The entire staff is very excited to be teaching CS 111 this semester and we're looking forward to meeting such a large and enthusiastic group of students. We want all of you to be successful here. Welcome to CS 111!