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CS255 Spring 2006 Sec1 Home Page/Syllabus

Design and Analysis of Algorithms

Instructor: Chris Pollett
Office: MH 214
Phone Number: (408) 924 5145
Email: cpollett@yahoo.com
Office Hours:MW 1:20pm-2:50pm 4:20-5:20pm
Class Meets:
Sec1 MW 5:30pm-6:45pm in MH234

Prerequisites

To take this class you must have taken: C155 with a grade of C- or better.

Texts and Links

Required Texts: Introduction to Algorithms, 2nd Edition. by Cormen, Leiserson, Rivest, and Stein. McGraw Hill. 2001.
Handout1-PDF.
Handout2-PDF. (We will also use the material in these two handouts.)
Online References and Other Links: Java 5 API Specification.
Obtaining LaTeX.
LaTeX Documentation.
LaTeX file with many examples.
JPicEdt for editing graphics for LaTeX.

Topics and Outcomes

This course covers the basics of randomized algorithms, parallel algorithms, distributed algorithms, algorithms related to the theory of NP-completeness, and approximation algorithms. Randomized algorithms are algorithms which make use of a random number generator. For instance, one fast way to check if a number is prime makes of such a generator. Parallel algorithms are algorithms which are designed to be partitionable with minimal overhead among many processors who share a global clock. Sorting networks to sort lists on polynomial processors in logarithmic time are examples of this. Distributed algorithms are algorithms designed to work on multiple processors which don't share a global clock. An example situation might be to get an algorithm to get a bunch of computers on a network to agree on a common value. NP problems are languages with polynomial time proofs of membership. For instance, given a potential factorization of a number we can in polynomial time check whether it is correct. NP-complete problems are problems in NP to which any other problem in NP can polynomially time reduced. We will consider different algorithms for during this kind of reduction. Approximations algorithms are usually efficient algorithms which approximately solve some optimization problem which is not known to have a efficient solutions. For instance, one might have an algorithm which approximately finds a traveling salesman tour. In addition to these algorithms, we will also go over the computer algebra algorithms neccessary to do basic cryptographic protocols such as RSA. By the end of this course, you should be able to code one example of a randomized algorithm, parallel algorithm, distributed algorithm, a polynomial time reduction, an approximation algorithm, and a computer algebra algorithm. For each of these types of algorithms, by the end of this course you should be able to do problems to analyse its run-time performance and correctness.

Below is a tentative time table for when we'll do things this quarter:

Week 1: Jan 25 Read 5.1
Week 2: Jan 30 , Feb 1 Read 5.2-5.4
Week 3: Feb 6 (HW1 due) , Feb 8 Read 27.1-27.3
Week 4: Feb 13 , Feb 15 Finish Chapter 27. Review
Week 5: Feb 20 (Midterm 1) , Feb 22 Start Handout1
Week 6: Feb 27 (HW2 due) , Mar 1 Finish Handout1, Read Sec 1 of Handout2
Week 7: Mar 6 , Mar 8 Read Handout 2 to Sec 3
Week 8: Mar 13 , Mar 15 Finish Handout 2
Week 9: Mar 20 , Mar 22 (HW3 due) Read 31.1-31.4
Week 10: Mar 27 , Mar 29 Spring Break
Week 11: Apr 3 , Apr 5 Finish Chapter 31
Week 12: Apr 10 , Apr 12 (Midterm 2) Review
Week 13: Apr 17 , Apr 19 Read 34.1-34.3
Week 14: Apr 24 (HW4 due) , Apr 26 Finish Chapter 34
Week 15: May 1 , May 3 Read 35.1-35.3
Week 16: May 8 , May 10 Finish Chapter 35
Week 17: May 15 Review
The final will be Monday, May 22 from 5:15pm-7:30pm

Grading

Homeworks 40%
Midterm 1 15%
Midterm 2 15%
Final 30%
Total100%

Grades will be calculated in the following manner: The person or persons with the highest aggregate score will receive an A+. As this is a graduate class the material will be harder, and so I will make a slightly more lenient curve than typical for an undergraduate class. The lowest scoring person with a score above 60 will be the cut-off for a B-. That is, that person will receive a B-, but no one below him will. The region between this high and low score will be divided into five equal-sized regions. From the top region to the low region, a score falling within a region receives the grade: A, A-, B+, B, B-. If the boundary between an A and an A- is 85, then the score 85 counts as an A-. Scores below the lowest B- but above 50 receive the grade C. Those below 50 receive the grade F.

If you do better than an A- in this class and want me to write you a letter of recommendation, I will generally be willing provided you ask me within two years of taking my course. Be advised that I write better letters if I know you to some degree.

Homework Info

Links to the current list of assignments can be found on the left hand frame of the class homepage. After an assignment has been returned a link to its solution (based on the best student solutions) will be placed off the assignment page. Material from assignments may appear on midterms and finals. For homeworks you are encouraged to work in groups of up to three people. Only one person out of this group needs to submit the homework assignment; however, the members of the group need to be clearly identified in all submitted files. Homeworks for this class will be submitted and returned completely electronically. The written and programming parts of an assignment are submitted by clicking on the submit homework link for your section on the left hand side of the homepage and filling out the on-line form. Hardcopies or e-mail versions of your assignments will be rejected and not receive credit. Homeworks will always be due by the start of class on the day their due. Late homeworks will not be accepted; however, your low homework score will be dropped.

When doing the programming part of an assignment please make sure to adhere to the specification given as closely as possible. Names of files should be as given, etc. Failure to follow the specification may result in your homework not being graded and you receiving a zero for your work. In addition, you should make sure your code conforms with the Departmental Java Coding Guidelines. This will be worth one point on every assignment.

The written part of each homework should be typeset in LaTeX. Links to where one can obtain LaTeX can be found in the Text and Links section above.

Exams

The midterms will be during class time on: Feb 20 and Apr 12 .

The final will be: Monday, May 22 from 5:15pm-7:30pm.

All exams are closed book, closed notes and in this classroom. You will be allowed only the test and your pen or pencil on your desk during these exams. Beeper or cell-phone interruptions will result in immediate excusal from the test. The final will cover material from the whole quarter although there will be an emphasis on material after the last midterm. No make ups will be given. The final exam may be scaled to replace a midterm grade if it was missed under provably legitimate circumstances. These exams will test whether or not you have mastered the material both presented in class or assigned as homework during the quarter. My exams usually consist of a series of essay style questions. I try to avoid making tricky problems. The week before each exam I will give out a list of problems representative of the level of difficulty of problems the student will be expected to answer on the exam. Any disputes concerning grades on exams should be directed to me, Professor Pollett.

Regrades

If you believe an error was made in the grading of your program or exam, you may request in person a regrade from me, Professor Pollett, during my office hours. I do not accept e-mail requests for regrades. A request for a regrade must be made no more than a week after the homework or a midterm is returned. If you cannot find me before the end of the semester and you would like to request a regrade of your final, you may see me in person at the start of the immediately following semester.

Academic Honesty

Plagiarism on homework or cheating on tests will result in appropriate academic disciplinary action being taken. You should not discuss or share code or problem solutions between groups! Information on the university policy governing academic dishonesty can be found at http://www2.sjsu.edu/senate/S04-12.htm. At a minimum a 0 on the assignment or test will be given. A student caught using resources like Rent-a-coder will receive an F for the course and be referred to University for disciplinary action.

Additional Policies and Procedures

The campus policy to ensure compliance with the Americans with Disabilities Act is:
"If you need course adaptations or accommodations because of a disability, or if you need special arrangements in case the building must be evacuated, please make an appointment with me as soon as possible, or see me during office hours. Presidential Directive 97-03 requires that students with disabilities register with DRC to establish a record of their disability."

More information about SJSU policies and procedures can be found at the following links: