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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, MATH 213, MATH 347, MATH 412 or MATH 413. Class Schedule Information: Students must register for one lecture-discussion and one lecture section.

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)

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)

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.