Syllabus

CS 427 Algorithm Analysis

Winter 2017

 

Objectives

This course is a study of algorithm design, algorithm complexity analysis, and problem complexity analysis. Design techniques analyzed will include divide-and-conquer, dynamic programming, greedy algorithms, backtracking, and branch-and-bound. These techniques can be considered general problem solving tools, whose applications are not limited to traditional computing and mathematical problems. Two factors make this point particularly important. First, more and more computing applications go beyond the traditional domain, and there are reasons to believe that this trend will strengthen in the future. Second, developing student’s problem solving skills has come to be recognized as a major goal of college education. Among all the courses in a computer science curriculum, a course on the design and analysis of algorithms is uniquely suitable for this task because it can offer a student specific strategies for solving problems. The course is organized around some fundamental strategies of algorithm design and algorithm design will be taught on a par with analysis. Some more abstract but very important topics will be also included: NP-completeness, approximation algorithms, lower-bound limits.

Learning Outcomes

On completion of this course, the student will have:

	·        A basic understanding of algorithm design and problem solving using fundamental techniques.
	·        The student will be able to demonstrate the associations between problem solving, algorithm design, and complexity analysis.
	·        Applied algorithm design, analysis, and implementation in various applications.
	·        Developed creativity and strategy skills for problem solving.

Grading

Midterm Exam	35%
Final Exam	37%
Assignments (approx. 30; likely only some of them will be graded). It is your best interest to work on all assignments, because there is a chance that the assignment that you may decide to skip will be graded or be a part of the exams for all students and you will get 0 for it in HW. Also have in mind that the number of topics covered in class (and needed for your future work!) is always greater than the number of topics that can be in HWs and exams. Thus, it is your best interest to learn at least all HW topics. Use instructor’s office hours and tine of TA during the labs to ask how correct your solutions are (especially not graded).	25%
Class participation (answering questions not only attending)	up to 3%

Grade Distribution:

[95 – 100]      A

[90 – 95)        A-

[87.5 – 90)     B+

[82.5 – 87.5)  B

[80 – 82.5)     B-

[77.5 – 80)     C+

[72.5 – 77.5)  C

[70 – 72.5)     C-

[67.5 – 70)     D+

[62.5 – 67,5)  D

[60 – 62.5)     D-

[0   – 60)         F

 

If you must miss an exam, contact your instructor prior to the exam to schedule a time to make it up. Late submission of assignments is generally not accepted. No partial credit for late assignments will be offered.

Lectures & Projects

The slides for lectures can be found in the shared directory on Neve\cs427. Be ready to spend about two hours to prepare for each class (Reading + Assignment). Exercises have hints at the end of the textbook!

Links

Courses on WWW

Dictionary of Algorithms and Data Structures

Dictionary of Computing

Data Structures and Algorithms many useful links by Prof. Toussaint

Course Schedule

(It can be updated. Check for updates before each assignment due date.)

 

Honor Code: All work turned in for credit, including exams and all components of the project, are to be the work of the student whose name is on the exam or project. For all project components, the student can receive assistance from individuals other than the instructor only to ascertain the cause of errors. Thus you can get help if you need it to figure out why something doesn't work. You just can't get help from anyone, other than the instructor or TA, to figure out how to make something work. All solutions turned in for credit are to be your individual work and should demonstrate your problem solving skills, not someone else's. The following text should appear on all assignments: I pledge that I have neither given nor received help from anyone other than the instructor for all program components included here.

You should write the code for your programs yourself including pseudo-code.  Writing it yourself is the only way you will learn. Do not work together to solve the programming assignments to the extent that two programs are essentially the same solution. All program solutions turned in for credit are to be your individual work and should demonstrate your problem solving skills, not someone else's. Since everyone is writing their own code, no two programs should be the same or so similar that I could convert one to the other by a simple mechanical transformation (e.g. changing variable names and comments). I consider this plagiarism and a violation of academic code.

First violation: Students must meet with the instructor. In most cases, the grade will be split between the authors of the copied programs. Second violation: Students will receive no credit for the assignment, an incident letter will be placed on file in the Computer Science Department, and the matter referred to the Computer Science Department Chair.

Class Attendance: Class attendance is expected and recorded.

 

ADA Statement: Students with disabilities who wish to set up academic adjustment in this class should give me a copy of their "Confirmation of Eligibility for Academic Adjustment" from the Disability Support Services Office as soon as possible so we can discuss how the approved adjustment will be implemented in this class. Students without this form should contact the Disability Support Services Office, Buillon 205 or dssrecept@cwu.edu or 963-2171.

 

Caveat: The schedule and procedures for this course are subject to change. It is the student's responsibility to learn of and adjust to changes.