CS 330 - Algorithms

Course links: Course website (lecture notes): https://faculty.digipen.edu/~dvolper/2026/spring.cs330/index.html everyone uses the same credentials: user/letsstudy Forum/public questions: Teams cs330-.....-combined here Code/homework related questions: cs330.volper.tas at digipen.edu Private questions: dvolper at digipen.edu Assignment/lab/quiz/exam submission: pontus use your SRS credentials.

Books (free):
Erickson
Shaffer

Required software

C++ compiler (g++, clang++, Visual Studio, etc.)

Syllabus (pdf)

week 1	Big-O Big-O review Big-O for data structures Iterative brute-force algorithms brute-force examples brute-force iterative algorithms lecture.brute.force.pdf iterative brute-force algorithms (old version)
05/12 (Tuesday) 05/14 (Thursday)

week 2	Recursive brute-force algorithms brute-force recursive algorithms backtracking variants from slides - download code used in slides recursion to iteration - how to convert recursive algorithms to iterative
05/19 (Tuesday) 05/21 (Thursday)

week 3	Empirical analysis Longest increasing subsequence sample Tools: here
05/26 (Tuesday) 05/28 (Thursday)

week 4	Greedy algorithms lecture.greedy.txt Dijkstra's algorithm - only positive weights allowed, 3 implementations example of Dijkstra's algorithm on a graph cs280 graph notes more details Kruskal algorithm Erickson: 4.1, 4.2, 4.3 Divide and conquer algorithms lecture.divide.conquer.txt merge sort example Erickson: 1.4, 1.5, 1.6
06/02 (Tuesday) 06/04 (Thursday)

week 5	Midterm on Thursday June 11. You are allowed to bring one 2-sided A4/Letter cheat-sheet. Topics: big-O and brute-force algorithms (iterative and recursive). sample.midterm.txt
06/09 (Tuesday) 06/11 (Thursday)

week 6
06/16 (Tuesday) 06/18 (Thursday)

week 7
06/23 (Tuesday) 06/25 (Thursday)

week 8
06/30 (Tuesday) 07/02 (Thursday)

week 9
07/07 (Tuesday) 07/09 (Thursday)

week 10
07/14 (Tuesday) 07/16 (Thursday)

week 11
07/21 (Tuesday) 07/23 (Thursday)

week 12 - final exams week

Assignments (may change as courses progresses): maximum subarray sum empirical analysis travelling salesperson (TSP) brute-force, recursive with best-first optimization closest pair divide and conquer electric Dijkstra greedy, modified Dijkstra algorithm electric Dijkstra 2 continuation of electric Dijkstra, binary search knapsack dynamic programming overlap scan line algorithm

maximum subarray sum	empirical analysis
travelling salesperson (TSP)	brute-force, recursive with best-first optimization
closest pair	divide and conquer
electric Dijkstra	greedy, modified Dijkstra algorithm
electric Dijkstra 2	continuation of electric Dijkstra, binary search
knapsack	dynamic programming
overlap	scan line algorithm