CIS 575, Introduction to Algorithm Analysis, Spring 2018

• Classes: MWF, 2:30pm-3:20pm, in Durland 1073.
• Instructor: Torben Amtoft, tamtoft hat ksu dot edu, Engineering 2179.
  Office Hours: Tuesdays from 1:30pm to 3pm, Thursdays from 3pm to 4:30pm, and by appointment.
• Teaching Assistant: Pruthvidhar Dhodda, pdhodda hat ksu dot edu
  Office hours: in DUE 1119/GTA Office, Tuesdays and Thursdays from 9am to 10:30am, and by appointment.
• Grader: Shanshan Wu, sswu hat ksu dot edu

• Course Homepage: http://people.cis.ksu.edu/~tamtoft/CIS575/S18/index.html.
• Up-to-date Log File: http://people.cis.ksu.edu/~tamtoft/CIS575/S18/log.html.
• Reading Material: Introduction to Algorithms, Thomas H Cormen & Charles E Leiserson & Ronald L Rivest & Clifford Stein, 3rd Ed., MIT Press, 2009.
  Suggested further reading (optional): Algorithms: A Top-Down Approach, Rodney Howell, 9th draft (available online).

• CIS 300 (Data and Program Structures)
• CIS 301 (Logical Foundations of Programming)
• MATH 510 (Discrete Mathematics)

• Significant programming experience in some high-level language, for example Java, C#, C, or C++
• Familiarity with standard data structures such as lists, stacks, trees, graphs, etc.
• Understanding of basic concepts of propositional and predicate logic and their use in program verification
• Experience in writing mathematical proofs in natural language
• Understanding of fundamental mathematics such as basic set theory, functions, solution of equations, limits, summations, derivatives and integrals, combinatorics

Learning Outcomes: Students should attain competency in the following:

• Application of mathematical techniques to analyze time and space usage of algorithms and data structures
• Understanding various advanced data structures and their tradeoffs
• Proving theorems about algorithms
• Recognizing and applying algorithmic design techniques

Topics:

• Algorithm correctness
• Worst-case asymptotic analysis
• Various data structures, such as
  • Graphs and trees
  • Priority queues
  • Union/find structures
• Various design techniques, such as
  • Divide-and-conquer algorithms
  • Greedy algorithms
  • Dynamic programming algorithms
• Certain frequently occurring settings, such as
  • Depth-first search
  • Network flow and matching

Homeworks are due almost every week and are to be submitted through Canvas.
Assignments that are late will be graded but, unless in case of documented medical or family emergencies, with a penalty of 20% per day (10% if submitted less than 12 hours after deadline).

Quizzes will be frequently given in class, using the iClicker system (instructions are uploaded on Canvas).

Exams will be closed-book though the use of a limited amount of note sheets may be permitted.
The final will be comprehensive, but with emphasis on the last part of the course.

Grading:

• Homework: 25 %
• Exam 1, February 21: 20 %
• Exam 2, April 4: 20 %
• Final Exam, May 9: 25 %
• In-class quizzes: 10 %

Final letter grades are not based on strict percentage cutoffs but are "curved" by taking into account the difficulty of the exercises and exams. As a rule of thumb, however, you should expect that it requires a bit more than 80 % to earn an A, and somewhat more than 60 % to earn a B. In general, my approach to grading is expressed well by this piece by S.A. Miller.

Grievances: If you think the instructor or the TA has made an oversight when grading your test or your homework, you are of course very welcome to ask for clarification. But complaints about judgment calls, like how much credit to give for a partially correct solution, are not encouraged (it is like arguing balls and strikes).

Academic Honesty: Kansas State University has an Honor & Integrity System based on personal integrity which is presumed to be sufficient assurance in academic matters one's work is performed honestly and without unauthorized assistance. Undergraduate and graduate students, by registration, acknowledge the jurisdiction of the Honor & Integrity System. The policies and procedures of the Honor System apply to all full and part-time students enrolled in undergraduate and graduate courses on-campus, off-campus, and via distance learning.

A component vital to the Honor & Integrity System is the inclusion of the Honor Pledge which applies to all assignments, examinations, or other course work undertaken by students. The Honor Pledge is implied, whether or not it is stated: "On my honor, as a student, I have neither given nor received unauthorized aid on this academic work."

A grade of XF can result from a breach of academic honesty. The F indicates failure in the course; the X indicates the reason is an Honor Pledge violation.

For more information, visit the Honor & Integrity System home web page at: www.k-state.edu/honor.

You are very welcome to discuss the course material, as well as specific questions, with your fellow students. However, all submitted answers must be your own work:

• You are not allowed to consult previous model solutions that may be around, or solicit the Internet for solutions to specific homework problems.
• You are not allowed to show your answers to, or look at the answers of, any other student --- this of course excludes any student that you have been allowed to team up with, but in such a case each of you must be able to understand and explain all parts of the submitted work.

Students with Disabilities: Students with disabilities who need classroom accommodations, access to technology, or information about emergency building/campus evacuation processes should contact the Student Access Center and/or their instructor. Services are available to students with a wide range of disabilities including, but not limited to, physical disabilities, medical conditions, learning disabilities, attention deficit disorder, depression, and anxiety. If you are a student enrolled in campus/online courses through the Manhattan or Olathe campuses, contact the Student Access Center at accesscenter@k-state.edu, 785-532-6441.

Expectations for Classroom Conduct: All student activities in the University, including this course, are governed by the Student Judicial Conduct Code as outlined in the Student Governing Association By Laws, Article V, Section 3, number 2. Students who engage in behavior that disrupts the learning environment may be asked to leave the class.

Acknowledgment: Much of the course material, including this syllabus, is adapted from a previous course taught by Rodney Howell.

Copyright 2018 (Torben Amtoft) as to all lectures. During this course students are prohibited from selling notes to or being paid for taking notes by any person or commercial firm without the express written permission of the professor teaching this course. In addition, students in this class are not authorized to provide class notes or other class-related materials to any other person or entity, other than sharing them directly with another student taking the class for purposes of studying, without prior written permission from the professor teaching this course.