CS 231 Data Structures & Algorithms

This course emphasizes reasoning about data structures and algorithms— understanding correctness, efficiency, and design tradeoffs—before implementing them in code.

Labs Projects Google Classroom Moodle CS Dept

Where do I go for…

Lab schedule, staff, check-ins, attendance → Labs
Project instructions, submission format, late policy → Projects
Lab check-ins & project submissions → Google Classroom
Weekly materials (slides, homework, quizzes, CodeRunner) → Moodle
Department resources → CS Department

Instructors

Instructor

Prof. Allen V. R. Harper

Lecturer (both sections)
Lab A instructor
Email: aharper [at] colby.edu
Office: Davis 311

Office Hours:
Monday: 9-10 AM 11-12 AM 1–4 PM
Wednesday: 9-10 AM 11–12 AM
Friday: 9-10 AM 11-12 AM

Instructor

Prof. Ike Lage

Lab B instructor
Email: ilage [at] colby.edu
Office: Davis 211

Office Hours:
Monday: 2:20–3:20 PM
Tuesday: 3:00–4:30 PM
Thursday: 11:00 AM–12:00 PM

Course Goals

Implement core data structures using object-oriented design principles.
Implement and analyze classic search, sort, and traversal algorithms using Big-O notation.
Make informed tradeoffs between alternative designs and implementations.
Use data structures and algorithms to solve computational problems appropriately.
Communicate results and explain algorithms clearly.

Grading

Component	Weight	Notes
Quizzes	35%	Weekly quizzes; lowest dropped + 1 retake (May 8th).
Final Exam	20%	Comprehensive assessment at the end of term.
Project Reflection Quiz	10%	Quiz on previous project; lowest quiz dropped.
Lab Checkpoint	10%	Implementing project's data structure.
Projects	10%	Solving larger-scale problems.
Extensions	10%	Student designed mini-projects.
Participation	5%	Attendance, Homework, in-class activities.

Final Exam (Sections A & B)

Date: Thursday, May 14th

Time: 6:00–9:00pm

Location: Lovejoy 100 (First Floor Auditorium)

Official College Policy (Registrar):

“Final examinations cannot be rescheduled to accommodate travel plans. Students should not make travel plans until they have full knowledge of their final examination schedule.”

Textbook

No required textbook. Lecture notes and code are posted on Moodle.

Optional free resource:
A Practical Introduction to Data Structures and Algorithm Analysis (Java), Clifford Shaffer