CSCI 256
Algorithm Design and Analysis Spring 2013
Division III Quantitative/Formal Reasoning
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Class Details

This course investigates methods for designing efficient and reliable algorithms. By carefully analyzing the structure of a problem within a mathematical framework, it is often possible to dramatically decrease the computational resources needed to find a solution. In addition, analysis provides a method for verifying the correctness of an algorithm and accurately estimating its running time and space requirements. We will study several algorithm design strategies that build on data structures and programming techniques introduced in Computer Science 136. These include induction, divide-and-conquer, dynamic programming, and greedy algorithms. Particular topics of study include graph theory, hashing, and advanced data structures.
The Class: Format: lecture
Limit: 40
Expected: 25
Class#: 3113
Grading: yes pass/fail option, yes fifth course option
Requirements/Evaluation: evaluation will be based on problem sets and programming assignments, and midterm and final examinations
Prerequisites: Computer Science 136 and Discrete Mathematics
Enrollment Preferences: current or expected Computer Science majors
Distributions: Division III Quantitative/Formal Reasoning
Attributes: BGNP Recommended Courses

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