CISC 320 Algorithms and Advanced Programming

Syllabus, Fall, 2010

Course meeting time: TR 11:00-12:15, place: 114 Pearson Hall

Saunders' office hours are 10-11am on Tuesdays and 9-10am Fridays in room 414 Smith Hall. Other meeting times can be easily arranged by email (please suggest a time when you first contact me).

Teaching Assistant: Sophie Che
Email: fei@cis.udel.edu
Office hours in room 103 Smith Hall: 10am-11, Mondays and Wednesdays

Text: Skienna, The Algorithm Design Manual, 2nd Edition, Springer, 2010

References:
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.

Objectives of the course

To develop a good working knowledge of important algorithms in several domains and the of the tools to analyse their performance characteristics. See topics list below.
To develop an appreciation for – and a good understanding of – general strategies of algorithm analysis and design.
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.
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.
To understand the relationship of algorithm to implementation, in particular to enhance skill with C/C++ programming.

Topics

Arithmetic for large integers, polynomials, and matrices. Application of arithmetic to cryptography. Graph algorithms. Algorithms of Selection, Sorting, and Searching in dynamic data sets. String matching. Computational Geometry. Parallel Algorithms.

Homework

Assignments will be distributed throughout the semester, for the most part on a bi-weekly basis and due on a Tuesday. Homework is due by 4:30 on the date given. Homework received after this but before 4:30 on the next class day (normally a Thursday) has a 20% penalty. Homework received after that but before the second following class (normally a Tuesday) receives a 40% penalty. After this point we return graded homeworks and no longer accept late homework. Timeliness on assignments is important for your understanding of the material. This is not a subject that is effectively learned with periods of neglect and periods of cramming.

The course homepage will contain a frequently updated record of homework and reading assignments and synopsis of lecture topics.

Exams

There will be

a midterm exam on Tuesday, October 19, and
a final exam on Tuesday, December 14, at 10:30am to 12:30pm in our classroom.

Grading

Homeworks - 35% more or less
Midterm - 20%
Final - 40%
Class attendance and participation - 5% more or less

Policy on plagiarism

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 not necessary or 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.

Corrections, suggestions and comments to saunders@udel.edu