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COMPUTER SCIENCE 261
COMPUTER SCIENCE II
I. Introduction
A. Catalog Description
This course is a continuation of the topics introduced in CSCI161. It provides an introduction to the study of fundamental data structures and their associated algorithms. Students will learn how to choose appropriate data structures and algorithms for particular problems. They will learn about lists, stacks, queues, trees, sorting, searching, abstract data types, and object-oriented programming using an object-oriented programming language. Prerequisites: CSCI 161 together with MATH 121 or 258; or permission of the instructor. Satisfies the Mathematical Reasoning core requirement.
B. Learning Objectives
1. Learn about data structures and their associated algorithms.
2. Be introduced to proofs of program correctness.
3. Continue the development of good programming style, including object-oriented methods.
4. Be introduced to more advanced methods of program design (including data abstraction, information hiding, and object-oriented design), debugging, and testing.
5. Learn the fundamentals of algorithmic analysis.
6. Work with other students on programming projects.
C. Prerequisites
1. Computer Science 161 together with Math 121, or 258. A grade of C- is required in the prerequisite courses.
II. Required Topics
A. Program Design
1. Top-down implementation, object-oriented design, testing and debugging techniques; Stub procedures and driver programs.
B. Simple Data Structures
1. Data abstraction. Basic implementation techniques and algorithms associated with stacks, queues, linked lists, and binary trees.
C. Arrays, Searching and Sorting
1. Unsorted lists: Insertion, deletion, and linear search
2. Sorted lists: Insertion, deletion, linear search, and binary search
3. Sorting: At least one O(n^2) algorithm, and one O(n log n) algorithm
II. Required Topics (cont.)
D. Linked Lists
1. Pointers
2. Traversal, insertion, deletion and search operations
3. Doubly-linked list representation and operations
E. Queues and Stacks
1. Array and linked list implementations
2. Insertion and deletion operations
F. Trees
1. Pointer representations of a binary tree
2. Binary search trees
3. Recursive binary tree traversals: inorder, preorder, and postorder
G. Analysis of Algorithms
1. Fundamentals of algorithm analysis, asymptotic behavior and space vs. time tradeoffs.
H. Program Verification
1. Loop invariants, mathematical induction, preconditions and postconditions.
I. Recursion
1. Recursive data structures and algorithms. When to use recursion and when not to.
J. Hash Tables
1. Hash functions
2. Collision-resolution policies
IV. Bibliography
D. Gries, The Science of Programming
E. Knuth, The Art of Computer Programming, Vols. I, II, III
L. Nyhoff C++ An Introduction of Data Structures
C. Shaffer A Practical Introduction to Data Structures and Algorithm Analysis
N. Wirth, Algorithms + Data Structures = Programs
(video) Sorting Out Sorting