CISC 320 Introduction to Algorithms

Skienna, The Algorithm Design Manual, 2nd Edition, Springer, 2010
Available in hardcover, paperback, and e-text forms to rent or buy.
Note that the book has strong reference value for the future.
We'll affectionately call the book "the Design Manual" or "DM" for short.

An evolving summary of course resources and lecture topics is maintained and is linked from the course Sakai website.

1. To develop a good working knowledge of important algorithms in several domains and the of the tools to analyse their performance characteristics.

2. To develop an appreciation for – and a good understanding of – general strategies of algorithm analysis and design.

3. To appreciate lower bound arguments, i.e., demonstrations of best possible performance properties for any algorithm to solve a given problem, regardless of whether an algorithm is known which achieves this best possible performance.

4. To learn the rudiments of complexity classes (classification of problems by difficulty rather than of their various solutions – algorithms – by cost). In particular,, to appreciate the P = NP question and understand the significance of the "NP Complete" concept.

5. To understand the relationship of algorithm to implementation, in particular to enhance skill with C/C++ programming and use of shared memory multiprocessing with OpenMP.

Exams, pencil and paper exercises, and programming assignments are intended to measure your individual performance and accomplishments in the course. The writeup and organization of the solutions you submit must be entirely your own. You may consult books, papers, and web sources for ideas. However this is usually neither necessary nor particularly recommended. Solutions you discover for your self, you own. They are much more memorable for exam time and for later life. Plagerism from other students in the course or from anyone else is not tolerated and will be prosecuted in the UD judicial system.

Design and analysis of algorithms: worst/average case analysis, proofs for correctness and performance of algorithms. Algorithmic strategies (divide and conquer, greedy methods, dynamic programming, etc.). Algorithms for searching, forming and traversal of strings, trees and graphs. Categorization of computational problems: classes P and NP. NP completeness.
PREREQ: MATH210 and a minimum grade of C- in CISC220.

Basse and Van Gelder, Computer Algorithms , Addison Wesley, 2000.
Cormen, Leiserson and Rivest, Introduction to Algorithms, McGraw-Hill & MIT Press, 1990.
Dasgupta, Papadimitriou, and Vazirani, Algorithms, McGraw-Hill, 2008.
Goodrich and Tamassia, Algorithm Design: Foundations, Analysis, and Internet Examples, Wiley, 2002.
Kleinberg and Tardos, Algorithm Design, Addison Wesley, 2006
Sedgewick, Algorithms in C++, Addison Wesley, 1992.