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Computer Science 212

Computer Science 212

Computer Science 212. Title: Data Structures and Algorithms Instructor: Harry Plantinga Text: Algorithm Design: Foundations, Analysis, and Internet Examples by Goodrich and Tamassia. Computer Science 212 Data Structures and Algorithms. The Heart of Computer Science Data structures

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755 views • 55 slides
Computer Science 212

Computer Science 212

Computer Science 212. Title: Data Structures and Algorithms Instructor: Harry Plantinga Text: Algorithm Design: Foundations, Analysis, and Internet Examples by Goodrich and Tamassia. Computer Science 212 Data Structures and Algorithms. The Heart of Computer Science Data structures

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692 views • 55 slides
CS 311 Design and Algorithms Analysis

CS 311 Design and Algorithms Analysis

CS 311 Design and Algorithms Analysis. Dr. Mohamed Tounsi mtounsi@cis.psu.edu.sa. Problems and Algorithms. Abstractly, a problem is just a function p : Problem instances -> Solutions Example: Sorting a list of integers Problem instances = lists of integers

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764 views • 45 slides
Analysis Tools

Analysis Tools

Analysis Tools. Jyh-Shing Roger Jang ( ??? ) CSIE Dept, National Taiwan University. Several Basic Functions. Polynomial Constant function Linear function Quadratic function Cubic function Logarithm function N-Log-N function Exponential function. Commonly used basic functions.

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332 views • 32 slides
Analysis of Algorithms

Analysis of Algorithms

Analysis of Algorithms. Input. Algorithm. Output. Running Time. Most algorithms transform input objects into output objects. The running time of an algorithm typically grows with the input size. Average case time is often difficult to determine. We focus on the worst case running time.

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414 views • 31 slides
Chapter 4 Analysis Tools

Chapter 4 Analysis Tools

Chapter 4 Analysis Tools. Objectives Experiment analysis of algorithms and limitations Theoretical Analysis of algorithms Pseudo-code description of algorithms Big-Oh notations Seven functions Proof techniques. Analysis of Algorithms. Input. Algorithm. Output.

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569 views • 30 slides
Running Time

Running Time

Running Time . The running time of an algorithm varies with the input and typically grows with the input size Average case difficult to determine We focus on the worst case running time Easier to analyze Crucial to applications such as games, finance and robotics. Experimental Studies.

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200 views • 19 slides

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