CS 225 - Data Structures

Spring 2024

TitleRubricSectionCRNTypeHoursTimesDaysLocationInstructor
Supplementary proj. for CS-225CS19922561879LAB01700 - 1750 M  0216 Siebel Center for Comp Sci 
Data StructuresCS225AH70578LAB01700 - 1750 M  0216 Siebel Center for Comp Sci Jeff Erickson
Brad R Solomon
Data StructuresCS225AL131208LEC41100 - 1150 M W F  AUD Foellinger Auditorium Carl Evans
Brad R Solomon
Jeff Erickson
Data StructuresCS225AL259777LEC41100 - 1150 M W F  AUD Foellinger Auditorium Carl Evans
Brad R Solomon
Jeff Erickson
Data StructuresCS225AYA31234LBD01300 - 1450 R  4029 Campus Instructional Facility Vivek Adrakatti
Ashna Rakhi Arya
Brad R Solomon
Carl Evans
Data StructuresCS225AYB31218LBD01300 - 1450 R  4025 Campus Instructional Facility Serena Trika
Brad R Solomon
Carl Evans
Jill Patel
Uday Kanth Reddy Kakarla
Data StructuresCS225AYC31222LBD01500 - 1650 R  4029 Campus Instructional Facility Abhilash Chander Potluri
Brad R Solomon
Carl Evans
Jill Patel
Tom Tian
Uday Kanth Reddy Kakarla
Data StructuresCS225AYD31225LBD01500 - 1650 R  4025 Campus Instructional Facility Serena Trika
Aditya Sinha
Brad R Solomon
Carl Evans
Mayank Shrivastava
Vivek Adrakatti
Data StructuresCS225AYE31227LBD01100 - 1250 R  4029 Campus Instructional Facility Kashob Kumar Roy
Abhilash Chander Potluri
Arthur Huang
Brad R Solomon
Carl Evans
Mayank Shrivastava
Data StructuresCS225AYF31229LBD01100 - 1250 R  4025 Campus Instructional Facility Thrivikraman Varadharajan
Aditya Sinha
Brad R Solomon
Carl Evans
Rishabh Adiga
Tom Tian
Data StructuresCS225AYG31231LBD01300 - 1450 F  0035 Campus Instructional Facility Thrivikraman Varadharajan
Ashna Rakhi Arya
Brad R Solomon
Carl Evans
Dhruv Mehta
Hao Guo
Data StructuresCS225ZJ168283LBD4 -    Volodymyr Kindratenko

Official Description

Data abstractions: elementary data structures (lists, stacks, queues, and trees) and their implementation using an object-oriented programming language. Solutions to a variety of computational problems such as search on graphs and trees. Elementary analysis of algorithms. Course Information: Credit is not given for CS 277 if credit for CS 225 has been earned. Prerequisite: CS 126 or CS 128 or ECE 220; One of CS 173, CS 413, MATH 213, MATH 347, MATH 412, or MATH 413. Class Schedule Information: Students must register for one lecture-discussion and one lecture section.

Learning Goals

Implement classic and adapted data structures and algorithms (1), (2), (6)
Navigate, organize, compile C++ projects of moderate complexity (many objects and dependencies) in Linux. (1), (2), (6)
Use basic editing and debugging tools such as GDB and Valgrind. (1), (2), (6)
Analyze the efficiency of implementation choices. (1), (2), (6)
Decompose a problem into its supporting data structures such as lists, stacks, queues, trees, etc. (1), (2), (6)
Diagnose appropriate approaches or algorithms to solve problems involving graph search, tree traversal, optimization, data organization, etc. (1), (2) , (6)

Topic List

C++ programming (compilation, classes, pointers, parameters, dynamic memory, memory management, inheritance, templates, generic programming)
Data structures - ADTS - (lists, stacks, queues, trees, dictionaries, priority queues, disjoint sets, graphs).
Data structures - implementation (linked memory, BST/AVL, B-tree, hash table, kd-tree, quad-tree, heap, union-find (up-trees), adjaceny list / arrays).
Algorithms (tree traversal, nearest neighbor, buildHeap, heapsort, BFS, DFS, MST, shortest paths)

Assessment and Revisions

Revisions in last 6 years Approximately when revision was done Reason for revision Data or documentation available?
Incremental changes to MPs 3/4 sp11 increase connections to surrounding curriculum (i.e. sorting, graph traversal) Informal discussion with CS125 Instructor (Angrave)
Lab exercises redesigned to be a) coupled tightly with lecture content, and b) tested and graded for credit. sp10 Success of labs depended on varied teaching skills of course staff, and they were optional, and thus poorly attended. Student feedback, ICES 08-10.
Grading policy changed to include credit for early submission of MPs, and also to provide nightly grading feedback. sp09 Motivate students to organize the assignment window more carefully. Informal discussion with CS225 course staff.
Addition of Parallel Lab Exercises (6 instructional hours) sp11 Parallel computing is pervasive. NSF/IEEE-TCPP Curriculum Initiative http://www.cs.gsu.edu/~tcpp/curriculum/?q=home
Developed CoMoTo - the collaboration monitoring toolkit. sp09 ongoing Observed increase in plagiarism. We wanted to increase the advising and counseling component of instruction while also maintaining the integrity of the course. GATE08
Increased discussion of applications of data structures. sp09 Broaden applicability of newly learned skills. Informal discussion with course owner Chekuri
Deployed a new educational software testing framework. fa11 Reduce the burden for understanding our given test code, allowing students to focus on the actual test cases. Informal discussion with CS225 course staff.

Required, Elective, or Selected Elective

Required.

Last updated

3/10/2019