CSCI 256 Spring 2013 Algorithm Design and Analysis (Q)

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.
Class Format: lecture
Requirements/Evaluation: evaluation will be based on problem sets and programming assignments, and midterm and final examinations
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Prerequisites: Computer Science 136 and Discrete Mathematics
Enrollment Preference: current or expected Computer Science majors
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Divisional Attributes: Division III,Quantitative and Formal Reasoning
Other Attributes: BGNP Recommended Courses
Enrollment Limit: 40
Expected Enrollment: 25
Class Number: 3113
CSCI256-01(S) LEC Algorithm Design & Analysis (Q) Division 3: Science and MathematicsQuantitative and Formal Reasoning Brent A. Heeringa
MWF 11:00 AM-11:50 AM Bronfman B34 3113
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