Computer Science: QR: Data Struc & Algorithms

Design and implementation of linear structures, trees and graphs. Examples of common algorithmic paradigms. Theoretical and empirical complexity analysis. Sorting, searching, and basic graph algorithms. Prerequisites: CS 110 with a grade of C- or better; minimum Sophomore standing.

Prereqs enforced by the system: C- or better in CS 110; Open to Degree and PACE students This course is taught in Brightspace, please see the expanded section description for more information

You will learn the common data structures for abstract data types and algorithms, including lists, trees, heaps, sorting, hashing, and disjoint set finding/uniting. You will also consider and compare their performances. Course goals and objectives: 1) You will gain knowledge of different data structures and recognize the use cases for each. 2) You will consider not just whether algorithms function correctly or not, but also their efficiency and performance as the amount of data grows. 3) You will use the C++ programming language to collect data with and analyze data structures and algorithms. This course is part of a pilot program that will be using Brightspace, UVM's new learning platform that's replacing Blackboard in Fall 2023. Since only a limited number of courses will be piloting Brightspace this coming semester, you are still likely to have courses in Blackboard as well. For more information on Brightspace: go.uvm.edu/brightspace-pilot

This is an in-person lecture course with practice problems and active learning activities sprinkled throughout. You will be expected to work for 6 hours outside of class each week, per University policy regarding work required for a 3 credit hour course.

Your final grade will be based on quizzes, programming projects, active learning exercises and participation, and a final exam.