CAS CS 237 - Probability in Computing - Spring 2026

Course Staff

Communication and Office hours

• Piazza is the primary platform for all online discussions, questions, and answers.
  • Use private posts for sensitive or specific questions regarding your solutions or personal matters.
  • Do not send emails to the course staff.
• We aim to maintain a positive and inclusive atmosphere on all course platforms.
• If you need special accommodations or are facing unusual circumstances during the semester, please reach out to an instructor privately via Piazza as early as possible.
  • For accommodations, forward relevant documentation from Disability and Access Services.
• Your suggestions for improving the course are always encouraged and appreciated.

• Check our Google Calendar for our Office hours.

Prerequisites

• CS 131 - Combinatoric Structures
• MA 123 - Calculus I
• CS 111 - Introduction to Computer Science I

We assume good working knowledge of elementary set theory and counting, elementary calculus (i.e., integration and differentiation), and programming in Python.

Syllabus

Introduction to basic probabilistic concepts and methods used in computer science. Develops an understanding of the crucial role played by randomness in computing, both as a powerful tool and as a challenge to confront and analyze. Emphasis on rigorous reasoning, analysis, and algorithmic thinking. This course fulfills a single unit in each of the following BU Hub areas: Quantitative Reasoning II, Critical Thinking.

Course structure

• Attendance in lectures and discussion is mandatory
• The two lecture sections of the course will be treated as one class. However, you must attend the section you are signed up for (please discuss with us if there is an issue).
• The content of the two lectures is identical, and assignments will be shared.

Textbooks

You can access both books for free or support the authors by purchasing the books.

• (LLM) Mathematics for Computer Science by Eric Lehman, Tom Leighton, and Albert Meyer.
• (P) Introduction to Probability, Statistics, and Random Processes by Hossein Pishro-Nik.
• (CLRS) Cormen, Leiserson, Rivest, and Stein. Introduction to Algorithms, Fourth Edition, MIT Press.

Schedule

This schedule is subject, and likely, to change as we progress through the semester. Reading chapters are from the first textbook (LLM) or from the second textbook (P), referred to by the acronyms of the author names.

Participation and Attendance

• Participation in lecture will be tracked with Top Hat. We will start using this in the second week of classes.
• Participation in discussion labs will be tracked with Top Hat as well.
• You will get full participation points if you answer at least 85% of the possible Top Hat questions. You do not need to answer correctly, although we encourage you to use these questions as exam preparation.
• You will get full attendance points if you attend at least 85% of the discussion labs.
• If you end up with x% points, where x < 85, you will get x/85 of the points.
• Most of the material covered in lectures and labs can be found in our textbooks. Read them!
• While our textbook will be very helpful, it is an imperfect substitute for in-class learning, which is the fastest (and easiest) way to learn the material.
• In all cases, you are responsible for being up to date on the material.

Homework Policy

• Submission: Weekly assignments are posted on Fridays and due by Thursday at 9:00 PM ET via Gradescope. A 3-hour grace period is allowed; submissions after this period will not be accepted.
• Content: Provide step-by-step explanations for your answers. Submissions with only answers will receive minimal credit.
• Formatting: Submit solutions as one single PDF file with high-quality images. Illegible submissions will receive a 0. We recommend using Dropbox for scanning.
• Gradescope Page Selection: Correctly select the pages for each problem on Gradescope. Failure to do so will result in a 10% penalty. If you don't have a solution, note "No solution provided."
• Late Policy: You may use up to 3 grace periods without penalty. After that, each late submission incurs a 1% penalty.
• Dropped Homework: The lowest homework grade will be dropped after penalties are applied. (Note that the intent of this is to allow you leeway on one emergency situation. Do not simply use your free dropped homework because you feel like it.)
• Academic Integrity and Collaboration:
  • The Collaboration & Honesty Policy outlines the rules of collaboration and penalties for cheating. All students are required to read, sign, and submit this document to Gradescope.
  • Submitting identically worded answers, including pseudocode, is a serious offense and will be reported to the Dean's Office (BU Academic Conduct Code).
  • Using ChatGPT or similar AI for homework solutions violates the Collaboration & Honesty Policy.
  • You are not required to cite material from the course textbook, lectures, discussion notes, or information provided by course staff.
  • For any other external information, a proper citation is required. Failure to cite constitutes plagiarism.
  • Explicitly searching for problem answers online or from individuals not enrolled in the current semester's class is strictly forbidden.
  • If you receive help on Piazza or during office hours from instructors for specific problems, you must list them as collaborators.
• Partial Submissions: Submitting partial work is acceptable if you cannot fully complete an assignment; avoid missing the deadline entirely.
• The instructors retain the right to oral explanation of any student work submitted for a grade. If the student cannot explain the work they have submitted, the instructor will assign a grade of 0 on the entire assignment in question.

Exams

• Both exams will consist of problem-solving and short questions about the material.
• Each exam duration and its location are given in the course schedule.
• The content of the final is cumulative.
• No collaboration whatsoever is permitted on exams, any violation will be reported to the College.
• Makeup exams will only be given in documented cases of serious illness.

Quizzes

• There will be four quizzes based on flashcards that will be posted weekly on Piazza. The quiz dates are posted on the schedule. The quizzes are all cumulative and will be simple short answers based on the flashcards. Quizzes will be held at the beginning of class and will last 10-15 minutes.
• Your lowest quiz score will be dropped. Similar to the homework, the intent of this is to give you leeway in an emergency situation.
• We use Anki for flashcards. You can download a free app at that link. We will also post the flashcards in plaintext if you prefer to print them out or just look at them on a website.

Grading

The course grade will be calculated as follows:

• 5% class participation
• 5% lab attendance
• 10% quizzes
• 20% weekly homework assignments
• 25% in-class midterm exam
• 35% in-class final exam. Don't make any travel plans before knowing all dates of your final exams.
• Incompletes for this class will be granted based on CAS Policy.
• Note: Optional homework problems do not count towards your course grade, but we will look at how you did on them if you ask for a recommendation letter.

Regrade Policy

• Regrade requests can be submitted up to one week (7 days) after grades for a given assignment have been posted (except the final exam).
• You must request a regrade via Gradescope, NOT through email.
• When we regrade a problem, your score may go up or down.

AI Policy

• As stated above, you may not use large language models like ChatGPT or Gemini to provide homework solutions. However, you may use them to help clarify concepts, discuss homework problems after you have submitted and the deadline has passed, or similar. Be wary, though, of hallucinations. It is good to double check any information you receive from LLMs with a reliable source.

Miscellaneous

LaTeX resources

• TexShop is a latex editor for the Mac platform;
• TexNiCenter is a text editor for Windows;
• Overleaf is a web-based latex system (that allows you to avoid latex installation on your machine).
• Not so short intro to latex;
• A latex tutorial.

Homework template files: tex, pdf, jpg.

FAQ

Many common questions have already been answered. Before emailing, posting on Piazza, or asking in class, please try the following:

1. Start with the syllabus. It answers an impressive number of questions about deadlines, policies, office hours, and grading. If you’re still unsure, feel free to consult an LLM. Copy-pasting the syllabus and asking “What is the policy on X?” is often faster than waiting for a reply—and helps keep Piazza focused on course content.

2. The course is taken as designed. Assignments and deadlines apply uniformly to everyone, except where formal accommodations are documented. See #1.

3. Missed a class? Something important was probably covered. Please check the posted materials and ask a classmate before reaching out. See #1.

4. Dates and deadlines have been posted since Day 1. Keeping track of them is part of the course. See #1.

5. Office hours exist! They’re a great place for questions about concepts, feedback, or anything not already answered in the syllabus. See #1.

6. Extensions are not granted. Instead, the course includes "grace periods" for flexibility—please use them wisely. See #1.

Reading the syllabus (or asking an LLM to summarize it for you) will save everyone time—including you. See #1.