CSE 310


Offered in:	Fall, Spring, and Summer
Credits:	3
Prerequisites:	CSE 205 , MAT 243

Data Structures and Algorithms

Course Description: This course covers advanced data structures and algorithms, including stacks, queues, trees (BST, B+), and graphs. Searching for graphs, hashing, and sorting.

Course Objectives:

Define data structures (types) such as heaps, balanced trees, hash tables.
Explain how to use a specific data structure in modeling a given problem (e.g. I can explain how to model a dictionary using balanced trees).
Identify, construct and clearly define a data structure that is useful for modeling a given problem.
State some fundamental algorithms such as merge sort, topological sort, Prim’s and Kruskal’s algorithm, and algorithmic techniques such as dynamic programming and greedy algorithms.
Use a specific algorithmic technique in solving a given problem (e.g. I can write a dynamic program that solves a shortest-path problem).
design an algorithm to solve a given problem
Define the notions of worst-case/best-case/average-case running times of algorithms.
Analyze and compare different asymptotic running times of algorithms.
Analyze a given algorithm and determine its asymptotic running time.
Combine fundamental data structures and algorithmic techniques in building a complete algorithmic solution to a given problem.
Create several algorithmic solutions to a given problem and choose the best one among them according to given requirements on time and space complexity

Useful Tools

These are some of the tools that are useful for this course (contributions welcome!)

ASU Linux Environment - Free CLI access to computers with Linux environment to compile and run code.
Heap Visualization
DSA Visualization
IKEA manuals for different algorithms - a fun way of getting more intuition for common algos, all without words. here’s BOGO SÖRT for example (check out KVICK SÖRT and MERGE SÖRT too!:

bogo sort

Student Reviews

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