Course Overview

Analysis, use, and design of data structures and algorithms using an object-oriented language like Java to solve computational problems. Emphasis on abstraction including interfaces and abstract data types for lists, trees, sets, tables/maps, and graphs. Implementation and evaluation of programming techniques including recursion. Intuitive and rigorous analysis of algorithms.

For more information, please see the course syllabus.

Course Information

Instructors: Owen Astrachan, Eric Fouh
Location: Griffith Theatre
Time: Mon/Wed 3:05pm - 4:20pm
Teaching Associate: Violet Pang
Graduate TAs: Eamon Ma
Undergraduate TAs: Noah Loewy (Lead/Front), Ally Doss (Lead/Front), Rishi Rao (Lead/Back), Rico Zhu (Lead/Back), Abigail Gurden, Albert Liu, Alina Yin, Angela Predolac, Asher Wallen, Austin Liu, Christopher Li, Cynthia Ma, Daniel Suh, Daria Plotz, Darian Salehi, Ella Gruenstein, Evan Wen, Jack Kugler, Jai Kasera, Jamie Tan, Janet Meng, Jasper Hu, Judy He, Kelly Xu, Leo Hu, Lucy Kopin, Mathew Chu, Nikhil Pesaladinne, Ren Staveteig, Riya Manchanda, Sabina Eraso, Shayaan Sameer, Theo Prosise

UTA info see uta page for photos/contact information

Office Hours:
Owen Astrachan - Monday 4:30-5:30 in D241/LSRC, Tuesday 10:00-11:00 in D241/LSRC or by zoom
Eric Fouh - TBD
Eamon Ma - TBD
Violet Pang - TBD
(See Ed for other office hours)
Links: Syllabus, Canvas, Gradescope, Ed, GitLab, Panopto

Grading

44% Exams
Three midterms and a final, each 11%, midterm can be replaced by corresponding part of final
26% Projects (7 or 8, later assignments weigh more than earlier)
Larger programming assignments, some done (optionally) in pairs
7% Discussion (14, each worth 0.5%)
Meet weekly, work collaboratively on contents and assignments
8% APTs
APTs: weekly small algorithmic programming problems
8% APT quiz (2, each is 4%)
Timed APTs demonstrating mastery of basic concepts
7% Engagement
includes WOTOs, DIY questions, pre-class questions