Syllabus

This document and linked resources are your primary source for understanding course expectations. Read it carefully and contact the instructor if you receive conflicting information from other sources.

Basic Facts

• Course Website: https://ucsb-cs24.github.io/s25
• Instructor: Diba Mirza
• Lecture: TR 12:30p - 1:45p, BUCHN 1940
• TAs: Ally Chu, Brenna Scholte, Daniel Lopez, Kali Hale, Sarah Hyatt
• ULAs: Cindy Zhao, Nikhil Kapasi, Olivia Chen
• Lab: 50-minute closed sections, Phelps 3525, F: 2p, 3p, 4p, 5p, and 6p

Lab attendance is optional but highly recommended, as TAs and LAs are available to assist and you must complete at least one mock interview with a TA or LA during these sessions. We may also use some of the office hour time for this. You may not switch sections because the class is full. If you have a conflict contact the instructor at the end of the first lecture. Start lab/programming assignments during sections and use office hours for additional support.

Contacting Staff: Use Ed for course-related communication, including private messages to staff or the instructor. For urgent emails, use diba@ucsb.edu with “CS24” in the subject line; expect a possible delay in response.

Overview

CS24 teaches efficient problem-solving with data structures and algorithms. You’ll explore abstract data types (e.g., stacks, queues, priority queues, sets, maps), their implementations (e.g., vectors, binary trees), and complexity analysis. You’ll also gain C++ proficiency, leveraging the Standard Template Library (STL) to prepare for technical interviews and future courses.

Prerequisites

CS24 builds on CS16. You should be comfortable with:

• Basic C++ data types (int, double, char, bool, string)
• Control structures (if/else, while, for)
• Function definition and parameter passing (by value, pointer, reference)
• Variable scope and lifetime
• The const keyword with parameters
• Arrays, C-strings, structs, and classes in C++
• Binary, decimal, octal, and hex conversions, and their relation to memory
• Recursion basics and when it’s appropriate

Review CS16 materials or consult TAs if needed as soon as possible.

Course Objectives

• Understand the C++ memory model (stack vs. heap allocation).
• Implement abstract data types (e.g., lists, trees) using object-oriented principles.
• Analyze algorithm and data structure efficiency with Big-O notation.
• Apply data structures to solve complex problems in C++.
• Master STL components for technical coding interviews.

Resources

All activities except programming assignments and exams are optional. Lectures are recommended, with slides and code on GitHub. Reading is primarily assigned from Main & Savitch.

• Textbooks:
  • Data Structures and Other Objects Using C++ by Michael Main and Walter Savitch (Reading assigned from this book, also the standard textbook for CS32)
  • [OP] *Open Data Structures C++ Edition * by Pat Morin (free at https://opendatastructures.org/)
  • [Dasgupta] Algorithms by Dasgupta and Vazirani https://cseweb.ucsd.edu/~dasgupta/book/toc.pdf
  • Problem Solving with C++ by Walter Savitch (CS16 standard textbook)
  • Data Structures and Algorithm Analysis in C++ by Mark Allen Weiss (CS 130A standard)
• Visualization: https://visualgo.net/
• C++ STL Documentation: https://en.cppreference.com
• Support: Instructor office hours (see website), TA/LA drop-in hours (Phelps 3525, times on course calendar)

In-Class Participation: Join iClicker Cloud at https://join.iclicker.com/AXZR. Participation is ungraded but encouraged.

Discussion Forum: Ed

Use Ed for Q&A (link on Canvas). Post public questions when applicable; for coding issues:

• Share the smallest relevant code snippet (not screenshots/photos).
• Make posts private if including significant code.

Grading

• LeetCode + Mock Interview: 10%
• Programming Assignments: 30% (labs + larger projects)
• Midterm: 25%
• Final Exam: 35%

A minimum 65% on the final exam is required to pass, ensuring core concept mastery. Below 65%, your grade is capped at D unless special circumstances apply (contact instructor). Letter grades (A, B, C, D, F) are set at the instructor’s discretion; A+ goes to the top 5%. Standard scale otherwise.

LeetCode + Mock Interview(10%)

Complete 10 medium LeetCode problems from the assigned list (on the course website) to build algorithmic skills aligned with course topics and exams.

• Setup: Create a LeetCode account (format: DS_[YourInitials]_[RandomNumber], e.g., DS_JD_1234).
• Submission: By Monday, Week 2, 11:59 PM, submit a Google Form (link on lab01) with your name, ID, and profile link.
• Task: Solve 10 problems, with at least one from each of the problem sets provided, by Friday, Week 9, 11:59 PM and complete one mock interview with TAs/LAs by the last office hour on Friday, Week 10.
• Grading: Grade for leetcode (5%) = (Accepted solutions / 10) * 10%, with at least 10 attempts (by the end of week 9) and completion of mock interview required for credit (e.g., 8/10 = 8%; < 10 attempted OR mock interview not completed = 0%). Grade for mock interview = 5%
• Monitoring: Progress may be checked (e.g., Week 5), but only the final count matters.

Schedule your mock interview early (signup form will be made available by week 2)

Late Policy

You have five late days total, with a maximum of three days per assignment, no penalty within this limit. Beyond this, a 10% deduction applies per day (up to one week), after which no credit is given unless approved for extenuating circumstances.

Pair Programming

Some assignments allow optional pair programming (2–3 students coding together at one terminal, like a lab partnership). Benefits include:

• Industry relevance and employer value
• Improved collaboration skills (feedback from UCSB CS employers)
• Enhanced learning and grades (research-backed, positive student feedback)
• Watch: http://bit.ly/pair-programming-video (10 min)

Use of AI Tools

AI tools (e.g., ChatGPT, GitHub Copilot, Grok) can support learning but must not replace your effort. Usage rules:

• Permitted Use: Allowed only for assignments labeled “AI-permitted” in instructions; prohibited elsewhere (e.g., exams, unmarked tasks).
• Constructive Engagement: Use AI to:
  • Clarify concepts (e.g., “Explain binary search trees”)
  • Get code feedback (e.g., “Improve my queue implementation”)
  • Explore design trade-offs (e.g., “Hash table vs. array pros/cons”)
• Prohibited Use: Generating full solutions, large code segments, or completing assignments (e.g., “Write a BST in C++”) is academic dishonesty, even when permitted. Debugging help is okay; rewriting your work is not.
• Documentation: Submit a log (e.g., text file or screenshots) of AI interactions for permitted assignments, showing constructive use and your own work. Earn up to a 5% assignment bonus on assignments where AI tools are permitted for thoughtful engagement (instructor’s discretion).
• Tool Choice: Any AI tool is allowed; identify it in your log.
• Consequences: Unauthorized use, missing logs, or misuse equals academic dishonesty (see below).

Academic Integrity

Check each assignment’s collaboration policy—some are individual, others allow pair programming. Review UCSB’s Academic Integrity guidelines: http://studentconduct.sa.ucsb.edu/academic-integrity. Violations (e.g., cheating, plagiarism, unauthorized AI use) result in:

• First Offense: Zero on assignment + one-letter grade drop
• Second Offense: Course failure
• All cases reported to the Office of Student Conduct

Key rules:

• No unauthorized materials, study aids, or services (see AI policy).
• Cite all sources, including web searches, in assignments.
• Keep graded work private (no public posting; Git repos must be private).
• Don’t share solutions outside your pair/group.
• No exam info from prior takers or non-approved sources (e.g., Chegg).
• Pair programming requires joint coding, not split work; submit one version on Gradescope with partner names.

Exam Makeups

Makeups are granted only for unavoidable emergencies (e.g., major illness), not scheduling conflicts. Check exam dates early!

Disabled Students Program (DSP)

UCSB accommodates students with disabilities via DSP (2120 Student Resource Building). Register early with documentation; accommodations are honored only through DSP. More info: http://dsp.sa.ucsb.edu.

Disclaimer

Policies are accurate but may change at the instructor’s discretion within UC guidelines.

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