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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 toward graduation 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 314, MATH 347, MATH 412, or MATH 413. Class Schedule Information: Students must register for one laboratory-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)

Required.