MATH 391 ST:Design & Analysis Algorithms

James Skon
Fall 2016
Location: Hayes 203, Time: 8:10-9:00, Days: MWF
People who analyze algorithms have double happiness. First of all they experience the sheer beauty of elegant mathematical patterns that surround elegant computational procedures. Then they receive a practical payoff when their theories make it possible to get other jobs done more quickly and more economically.” Donald E. Knuth

Objectives

This course introduces students to the analysis and design of computer algorithms. Upon completion of this course, students will be able to do the following:

  1. analyze the asymptotic performance of algorithms;
  2. demonstrate a familiarity with major algorithms and data structures;
  3. apply important algorithmic design paradigms and methods of analysis; and
  4. synthesize efficient algorithms in common engineering design situations.

Prerequisite: MATH 222 and SCMP 118 or PHYS 270 or equivalent.

Course Information

James SkonOffice Hayes Hall 303Office Hours: MTWHF 10:00-11:00Phone: (740) 427-5369Textbook: Introduction to Algorithms, 3rd Edition, MIT Press, Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, Clifford Stein, ISBN 0262033844Room and Time: Hayes 203, Time: 8:10-9:00, Days: MWFPaperless: This course is intentionally paperless. All assignments are turned in online through Moodle. The instructor will normally not accept work written or printed on paper. (Any excepts must be pre-approved by the instructor).41-1VkO1lL._SX359_BO1204203200_.jpg

Course Grades

Class Attendance/Participation10%
Problem Sets30%
LeetCode Assignments20%
Exams20%
Final Project/Presentation20%

Email help

While students are encouraged to use office hours instead of email, the instructor will respond to short questions when appropriate. In order to ensure that they will be correctly handled by the instructor’s filter, the subject of all emails must start with “MATH 391:”; any email without this header runs the risk of being filtered.

Lectures and Lecture Slides

Lecture slides will be available on this site by the day of the presentation. They are intended to help you reconstruct the work from class, but are not intended as a substitute for taking notes.

Readings

It is expected that you have read the assigned reading BEFORE class. We will be discussing the topic, and each student is expected to contribute to the conversations. Your participation grade will be partially dependent on your involvement in the discussions.

Problem Sets

Due date: Unless otherwise stated, Problem Sets are due by 5:00pm the day before they will be presented in class. There will be a 12 hour grace period during which the student will received a penalty equal to 5% of the value of the assignment; any assignments submitted more than 12 hours late will not be accepted. Exception: Each student may have a 24 hour extension on one assignment without penalty. This extension will be applied to the first assignment submitted outside the grace period (or retroactively used to cancel one grace-period penalty if not used by the end of the semester.)

Submission Methods: Assignments must be typed and submitted through the Moodle website. The instructor will not accept submissions through email, Moodle submissions in any format other than pdf, or hard copies submitted directly to him.

Missing Assignments: Problem sets are an important part of this class; the effort spent on them is a crucial part of the learning process. Failure to submit assignments is unacceptable: students earning 0s on two assignments cannot receive a grade higher than a B- for the course; students earning three 0s will receive an automatic F for the course.

Problem Set Work Teams: Two person teams may be randomly assigned for some problem sets. The teams should work together, discussing the solutions. However, each team member is responsible to write up their own solution and turn is in. Thus while teams may share the same solution, they also may might be the same. Each assignment will include an estimation of the percentage of work done but each member (from the perspective of each person). For example: “Work distribution: Carmen: 55%, myself: 45%”. The instructor will monitor this for patterns across multiple partners.

Problem Set Presentations: Each team must prepare to make a presentation of each problem. The instructor will review these before class, and determine which team will present which problems. The students class participation grade will depend in part of the level of preparation for the solution presentation.

Presentations: Students should be prepared to present and discuss their solutions formally in class the day specifies in the schedule.

LeetCode Assignments

Due Date: As with problem sets, the assignments are due by 5:00pm the day before they will be presented in class, with wth same rules for lateness.

Submission Methods: Assignments ust be submitted online with source code, runs showing a variety of test cases that demonstrate all major aspects of the problem space, a writeup of the computational and space complexity as requested in the assignments.

Collaboration: Students should conform to the “group work” policy below.

Presentations: Students should be prepared to present and discuss their solution formally in class the day specifies in the schedule. Be prepared to justify the solutions correctness as well as it computational analysis.

Programming Contest (extra credit)

While it is not required, it is highly encouraged that you participate in the ACM programming contests, first the one here at Kenyon on Sept. 24, and then in the one at YSU on November 4 and 5.

If you fully participate in the September 24 contest you will receive a 2% overall course bonus that will count against any points lost. If you participate in both the September 24 contest AND and November 5 contests you will receive a total % overall course bonus. (You cannot participate in the latter contest without being in the former).

Collaboration

In order to facilitate learning, students are encouraged to discuss homework and LeetCode problems amongst themselves. Copying a solution is not, however, the same as “discussing.” A good rule of thumb is the “cup of coffee” rule. After discussing a problem, you should not take away any written record or notes of the discussion. Go have a cup of coffee or cocoa, and read the front page of the newspaper. If you can still re-create the problem solution afterward from memory, then you have learned something, and are not simply copying. (The “group problems” are exempt from this, as they are intended to be done together.)

Term Project

20% of your grade will consist of a semester long research project, collimating in a 30 minute presentation at the end of the class. This project can be one of the following two types:

  1. (Theory) A review, analysis, and presentation of a relatively recent algorithm of some notability (something from the past 5-10 years). This should include a comprehensive explanation of the algorithm operation and complexity (space and time), a comparison with other techniques, and a review of the proof of both the analysis and the correctness of the algorithm.
  2. (Practice) The implementation, analysis, and testing of some significant algorithm technique or method not explored in this class. You find a problem from this class, or from work you have done or are doing elsewhere, and explore the use of one or more advanced algorithmic technique. This should also include an actual comparative runtime comparison with other techniques varying both the problem size, and the type, of the datasets.

The results of either will be presented during the finals period in a 30 minute time slot. The presentation will be evaluated by both the instructor, and the other students.

Two person teams can be considered for this project, but you must justify this option with clear evidence that it is significantly more work then a single person project. For example, you could explore and compare two distinct approaches, or do a combination of 1 & 2 above, or explore something that has significant complexity in and of itself.

Possible Sources: link

Plagiarism

All work turned in is expected to be your own. It is likely that proof, algorithm and code solutions for most problems exist online. Generally you should not search for any of these solutions. If you do use online or written documents, you must fully disclose and reference everything used, and be prepared to lose some credit if the help is deemed to be beyond that which you should used. The rule of thump is you can use references to help understand the problems and terminology, but should not use (and copy or modify) complete or partial solutions found online. Plagiarism detection methods may be used for detection of copying, and student will be subject to AIB notification in such cases.

Links

DateLecture ContentReadingNotes/LinksQuizSlidesAssignment Due
 Review the slides. It is you responsibility to be familiar with the following:
LogarithmsGraphsProof notationPseudocodeHeapsArray v. Lists
   review.basic_tools.pptx 
Aug 26IntroductionJoseph FlaviusCourse DetailsCh 1Josephus 01intro.pptx 
Aug 29Programming EnvironmentNetBeansLeetCode Bring Laptop to class!
NetBeansLeetCode344. Reverse Bits389. Find the Difference
   
Aug 31Proof By InductionProof: TilingProof: A tree of n nodes has n-1 edgesCh 2  02induction.pptxLeetCode0
Sept 2Present LeetCode 1 solutionsProof By Induction(Faulty) Proof: Right-handed people do not existProof: Candy Bars   03InductionPrograms.pptxLeetCode1
Sept 5Proof By Induction:Proving programs correct by induction   AlgorithmProofs.pptx 
Sept 7Graph TheoryCh 22  GraphTheory.pptx 
Sept 9Graph Theory Proof Example Present LeetCode 2 solutionsCh 23Course Project Instructions  LeetCode2
Sept 12Present Problem Set 1 Solutions    Problem Set 1
Sept 14Greedy Algorithms
Disjkstra’s Algorithm
   dijkstra.pptx 
Sept 16Greedy AlgorithmsClassroom Scheduling   intervalScheduling.pptx
knapsack.pptx
 
Sept 19Runtime AnalysisAsymptotic notationWorst-case analysisBinary searchProblem boundsPresent Problem Set 2 SolutionsCh 3   Problem Set 2
Solutions
Sept 21Runtime Analysis.Ch 3  asymptotic.pptx 
Sept 23Project Overview
Runtime Analysis
     
Sept 26Greedy AlgorithmsOverviewHuffman CodesCH 16  greedyOverview.ppt 
Sept 28Huffman Codes
Heaps and Priority Queues
Ch 17   LeetCode3
Problem Set 3
Sept 30Minimum Spanning TreesPrim’s AlgorithmKruskal’s AlgorithmUnion-Find StructureCh 22, 23  kruskal.pptxPresentation Topic Submit
Oct 3More on Union-Find and MST
Midterm Questions
 01UnionFind.pdf   
Oct 5Exam 1 Exam Study Guide   
Oct 7Midterm Break     
Oct 10Divide and ConquerSortingCh 4, 7MidtermSolutions.pdf DivideConquer.pptx 
Oct 12Analyzing Recurrence relationsCH 4.5  recurences.pptxLeetCode4
Oct 14A visit to the Art Show. RAFAEL
LOZANO-HEMMER

Navier–Stokes equations in JavaScript
  Problem Set 4
Moodle
Oct 17Analyzing Recurrence relationsCH 4  recurences.pptx 
Oct 19Analyzing Recurrence relationsCH 4Master Theorem recurences.pptx 
Oct 21Analyzing Recurrence relationsCH 4    
Oct 24Divide and conquerInversion CountingMinimum Distance4DivideAndConquerNotes.pdfInversionCounting.pptx closestpoint.pptx Problem Set 5 MoodlePresentation Status Report
Oct 26Linear Sorting8Count Sort VisualizationRadix Sort VisualizationBucket Sort VisualizationConvex Hall VisualizationConvex Hall using Graham linearsorting.pptxLeetCode5
Oct 28Dynamic ProgrammingIntroduction15  dynamic-programming.ppt 
Oct 31Dynamic ProgrammingLinear Sorting15   LeetCode6
Nov 2Dynamic ProgrammingRodcutting15  rodcut.pptx 
Nov 4Dynamic ProgrammingWeighted Interval Selection   weighted_interval_selection.pptxLeetCode7
Nov7Dynamic ProgrammingRussian Doll Envelope15Russian Doll Envelope  Problem Set 6
Nov 9Searching
Hashing
11  HashingIntro.pptLeetCode8
Nov 11Searching
Hashing Consideration
11  HashingConsiderations.pptPresentation Outline
Nov 14Present Problem Set 6 SolutionsPresent LeetCode 8 solutions Exam 2 Study Guide   
Nov 16Tree Structures12&18B-Tree Simulation
B+ Tree Simulation
 Trees.pptx 
Nov 18     Problem Set 7
Nov 21-25Thanksgiving Break     
Nov 28Exam 2    LeetCode9
Nov 30P and NP, nondeterminism, reductions34  AlgorithmicIntractability.pptx 
Dec 2P and NP, nondeterminism, reductions34Reduction Video AlgorithmicIntractability.pptx 
Dec 5ReductionsSubset SumHamiltonian Path*   SubsetSumProof.ppt 
Dec 7Reductions    Problem Set 8 Moodle
Dec 14Final Presentations 1:30 Presentation Time Sign Up PresentationGradingRubricPresentationPeerEvaluationMoodle link to turn in presentation

Statement on Title XI

Kenyon College seeks to provide an environment that is free of gender bias, discrimination, and harassment. If you have been the victim of sexual harassment/misconduct/assault,
interpersonal violence, or stalking we encourage you to report this. If you report this to a faculty member, she or he must notify Kenyon’s Title IX coordinator of any information about the incident that you provide. Kenyon College’s Title IX and VAWA Policy is available at: http://www.kenyon.edu/directories/offices-services/title-ix/policy/

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