James Skon
Spring 2019
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:
- analyze the asymptotic performance of algorithms;
- demonstrate a familiarity with major algorithms and data structures;
- apply important algorithmic design paradigms and methods of analysis; and
- synthesize efficient algorithms in common engineering design situations.
Prerequisite: MATH 222 and SCMP 118 or PHYS 270 or equivalent.
Course Information
| James Skon Office Hayes Hall 303 Office Hours: MTWHF 10:00-11:00 Phone: (740) 427-5369 Textbook: Introduction to Algorithms, 3rd Edition, MIT Press, Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, Clifford Stein, ISBN 0262033844 Room and Time: Hayes 203, Time: 8:10-9:00, Days: MWF Paperless: 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). |
Course Grades
| Class Attendance/Participation | 10% |
| Problem Sets | 30% |
| LeetCode Assignments | 20% |
| Exams | 20% |
| Final Project/Presentation | 20% |
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:
- (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.
- (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
- Leetcode – Site for solving interesting problems
- Puzzles for Computer Scientists
- Geeks for Geeks Practice
- Big-oh Cheat Sheet
- VisuAlgo.net – visualising data structures and algorithms through animation
- Data Structure Visualization
- Closed Hashing Simulator
- Algorithm Simulator
| Day | Lecture Content | Reading | Notes/Links | Slides | Assignment Due |
| Review the slides. It is you responsibility to be familiar with the following: LogarithmsGraphsProof notationPseudocodeHeapsArray v. Lists | review.basic_tools.pptx | ||||
| 1 | Introduction Joseph FlaviusCourse Details | Ch 1 | Josephus | 01intro.pptx | |
| 2 | Programming Environment NetBeansLeetCode | Bring Laptop to class! NetBeansLeetCode344. Reverse Bits389. Find the Difference | |||
| 3 | Proof By Induction Proof: TilingProof: A tree of n nodes has n-1 edges | Ch 2 | 02induction.pptx | LeetCode0 | |
| 4 | Present LeetCode 1 solutions Proof By Induction (Faulty) Proof: Right-handed people do not existProof: Candy Bars | 03InductionPrograms.pptx | LeetCode1 | ||
| 5 | Proof By Induction: Proving programs correct by induction | AlgorithmProofs.pptx | |||
| 6 | Graph Theory | Ch 22 | GraphTheory.pptx | ||
| 7 | Graph Theory Proof Example Present LeetCode 2 solutions | Ch 23 | Course Project Instructions | LeetCode2 | |
| 8 | Present Problem Set 1 Solutions | Problem Set 1 | |||
| 9 | Greedy Algorithms Disjkstra’s Algorithm | dijkstra.pptx | |||
| 10 | Greedy Algorithms Classroom Scheduling | intervalScheduling.pptx knapsack.pptx | |||
| 11 | Runtime Analysis Asymptotic notationWorst-case analysisBinary searchProblem bounds Present Problem Set 2 Solutions | Ch 3 | Problem Set 2 Solutions | ||
| 12 | Runtime Analysis. | Ch 3 | asymptotic.pptx | ||
| 13 | Project Overview Runtime Analysis | ||||
| 14 | Greedy Algorithms OverviewHuffman Codes | CH 16 | greedyOverview.ppt | ||
| 15 | Huffman Codes Heaps and Priority Queues | Ch 17 | LeetCode3 Problem Set 3 | ||
| 16 | Minimum Spanning Trees Prim’s AlgorithmKruskal’s AlgorithmUnion-Find Structure | Ch 22, 23 | kruskal.pptx | Presentation Topic Submit | |
| 17 | More on Union-Find and MST Midterm Questions | 01UnionFind.pdf | |||
| 18 | Exam 1 | Exam Study Guide | |||
| 19 | Midterm Break | ||||
| 20 | Divide and Conquer Sorting | Ch 4, 7 | MidtermSolutions.pdf | DivideConquer.pptx | |
| 21 | Analyzing Recurrence relations | CH 4.5 | recurences.pptx | LeetCode4 | |
| 22 | A visit to the Art Show. | RAFAEL LOZANO-HEMMER Navier–Stokes equations in JavaScript | Problem Set 4 Moodle | ||
| 23 | Analyzing Recurrence relations | CH 4 | recurences.pptx | ||
| 24 | Analyzing Recurrence relations | CH 4 | Master Theorem | recurences.pptx | |
| 25 | Analyzing Recurrence relations | CH 4 | |||
| 26 | Divide and conquer Inversion CountingMinimum Distance | 4 | DivideAndConquerNotes.pdf | Problem Set 5Moodle Presentation Status Report | |
| 27 | Linear Sorting | 8 | Count Sort Visualization Radix Sort Visualization Bucket Sort Visualization Convex Hall Visualization Convex Hall using Graham | linearsorting.pptx | LeetCode5 |
| 28 | Dynamic Programming Introduction | 15 | dynamic-programming.ppt | ||
| 29 | Dynamic Programming Linear Sorting | 15 | LeetCode6 | ||
| 30 | Dynamic Programming Rodcutting | 15 | rodcut.pptx | ||
| 31 | Dynamic Programming Weighted Interval Selection | weighted_interval_selection.pptx | LeetCode7 | ||
| 32 | Dynamic Programming Russian Doll Envelope | 15 | Russian Doll Envelope | Problem Set 6 | |
| 33 | Searching Hashing | 11 | HashingIntro.ppt | LeetCode8 | |
| 34 | Searching Hashing Consideration | 11 | HashingConsiderations.ppt | Presentation Outline | |
| 35 | Present Problem Set 6 SolutionsPresent LeetCode 8 solutions | Exam 2 Study Guide | |||
| 36 | Tree Structures | 12&18 | B-Tree Simulation B+ Tree Simulation | Trees.pptx | |
| 37 | Problem Set 7 | ||||
| Thanksgiving Break | |||||
| 39 | Exam 2 | LeetCode9 | |||
| 40 | P and NP, nondeterminism, reductions | 34 | AlgorithmicIntractability.pptx | ||
| 41 | P and NP, nondeterminism, reductions | 34 | Reduction Video | AlgorithmicIntractability.pptx | |
| 42 | ReductionsSubset SumHamiltonian Path | SubsetSumProof.ppt | |||
| 43 | Reductions | Problem Set 8Moodle | |||
| Final Presentations 1:30 | Presentation Time Sign Up | PresentationGradingRubric PresentationPeerEvaluation | Moodle link to turn in presentation |
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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,
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