Syllabus CS521 Data Structures and Algorithms 1

Course

CS 521 Data Structures and Algorithms 1

Term and Credits

  • Summer 2024
  • 3 Credits

Room and Time

  • Room: TBD
  • Day: Tuesday
  • Time: 6:00PM-8:50PM
  • Lecture will be streamed on Zoom and also Echo 360. Recordings will be made available using Echo 360.

Instructor

  • Joseph Gallego
  • Electronic Mail Address: jg3959@drexel.edu
  • Office: --
  • Extension: -
  • Office Hours: 4-5PM Friday Only Zoom (check Blackboard for the Link).

Course Description

This course is intended as a broad graduate-level introduction to the design and analysis of algorithms for some of the most frequently encountered combinatorial problems.

Course Objective and Goals

The course aims to provide familiarity with general algorithmic techniques, performance measures, analysis and problem areas.

Prerequisites

Some exposure to the topic at the undergraduate level and some general mathematical background and maturity are assumed. You should already have some:

  • basic knowledge of algorithms
  • basic proof knowledge
  • growth functions and asymptotic notation
  • recurrences
  • probabilistic analysis
  • sorting
  • median and order statistics
  • elementary data structures.

Topics

  • Asymptotic Analysis of algorithms.
  • Combinatorial Algorithms for searching and sorting.
  • Heaps; Binary Search Trees; Red-Black Trees; etc.
  • Basic graph algorithms - depth-first and breadth-first search; Minimum Spanning trees; bi-connected components; shortest paths; etc.
  • Dynamic Programming
  • Data Structures

Audience and Purpose within Plan of Study

This course is for graduate students with little prior knowledge of data structures and algorithms. It serves to give such students a firm foundation for future graduate study, and it is a requirement of the Computer Science Minor and Computer Science Post Bachelor Certificate degree programs.

Prerequisites

CS504 is a required co/prerequisites.

What Students Should Know Prior to this Course

What Students will be able to do upon Successfully Completing this Course

  • Students will be able to analyze algorithms.
  • Students will understand a set of fundamental algorithms and how to apply them.
  • Students will understand fundamental data structures and when to use each.
  • Students will be able to explain why algorithms are efficient and correct solutions to problems.
  • Students will be able to determine the applications and limits of data structures and algorithms.
  • Students will understand how complex computation is built from simple components.

Textbook

Algorithms Illuminated: Part 1: The Basics

  • Author: Tim Roughgarden
  • Published: 2017
  • ISBN: 978-0999282908

Algorithms Illuminated: Part 2: Graph Algorithms and Data Structures

  • Author: Tim Roughgarden
  • Published: 2018
  • ISBN: 978-0999282922

Algorithms Illuminated: Part 3: Greedy Algorithms and Dynamic Programming

  • Author: Tim Roughgarden
  • Published: 2019
  • ISBN: 978-0999282946

Algorithms Part 1

  • Author: Robert Sedgewick and Kevin Wayne

Algorithms Part 2

  • Author: Robert Sedgewick and Kevin Wayne

Introduction to Algorithms 4th Edition

  • Author: Thomas H. Comern, Charels E Leiserson etc

Course Material

Attendance

  • Face-to-face students must attend each class and sign in on a signature sheet.
  • Online students have to watch the entire echo360 video. I can see if you have watched the entire video.
  • Online students which take the live session will not have to watch the lecture video.

Lectures/Readings

  • Recorded videos will be posted for each lecture in learning.drexel.edu
  • Lectures will be held in the Classroom. They will be streamed using Zoom and Echo 360. A recording will be posted in the Echo 360 Section of BBLearn.

Homework Assignments

  • Homework will contain both written and programming questions.
  • Homework will be submitted using Blackboard (Written)
  • Homework Assignments are due on Tuesday at 05:59PM
  • Homework Assignments are to be completed individually.
  • Homework will be written using Latex.

Extra Credit

  • In this course, we value the course survey results. It is important for you to receive grades so you can determine how you are performing in class. We also want to know how we are doing. The course survey is our most important tool for determining how the students feel about the class. We also understand that completing the survey takes time and effort. Due to the importance of the course survey, extra credit will be provided to those students who complete it and provide evidence it has been completed. The extra credit will be 1 point added to the final grade for the class. This will take place at the end of the term.

Discord

  • This term, we will be using the CCI Discord Server instead of a discussion board.
  • You will be added automatically by Drexel CCI Support (iCommons). If you have any issues contact ihelp@drexel.edu

Late Submissions

  • Each student has two "late passes".
  • A student may exchange one of their late passes for an one day extension on any assignment.
  • Contact the TA/Professor to request one of your late passes be used.
  • You may use both late passes of the same assignment to get a 2 day extension.
  • A late pass must be requested no later than 24 hours after the original due date for the assignment.
  • Without late passes, -10 points per day with a max penalty of 100 points on an assignment. Late Submissions may be made until September 1, 2024 at 11:59PM.

Resubmissions

  • You may resubmit an assignment after you receive a grade. It will be regraded but a late penalty will be applied as if the resubmission date was the date of the original submission.

Special Circumstances

  • If you have a documented reason why you cannot submit an assignment by the deadline, a special exception may be made. The Professor may also waive the late submission penalty for documented special exceptions.

Course Policies

Academic Honesty Policy

The CCI Academic Honesty policy is in effect for this course. Please see the policy at http://drexel.edu/cci/resources/current-students/undergraduate/policies/cs-academic-integrity/. Academic Honesty Violations will be reported to the University. Punishment will be determined by the severity of the incident. Punishments include, but are not limited to,

  • Failing grade for class
  • Deduction of one letter grade
  • Zero on Assignment/Exam Violation took place on

Grading and Policies

  • 8 Homeworks 48% (6% each one)
  • Midterm exam 21%
  • Final exam 31%
  • Attendance 0%
  • Survey 1%

Keep in mind that the percentage sum up to 106. There are 6% extra credit for this class.

Final grades will be determined by your total points weighted according to this distribution. Grades may be curved but are generally computed via the formula below. It may be modified at the instructor's sole discretion, but letter grades will generally not be lower than those shown here.

- [100-97] A+
- (97-93] A
- (93-90] A-
- (90-87] B+
- (87-83] B
- (83-80] B-
- [80-77] C+
- (77-73] C
- (73-70] C-
- (70-67] D+
- (67-60] D
- (60-0] F

Tentative Course Schedule

Please see the appropriate assignment webpages for a detailed description of course deliverables.

Week Start Date Topic Assignments
1 6/24/2024 Why are you here? - HW 1 - Due Monday 7/1 at 11:59PM
Proof and Induction 101 class - Pre-lecture 1
(Online Class Through Zoom)
Additional reading: AI Part I 1.1,
1.2, 1.3, 3.1
2 7/1/2024 Asymptotics, Worst-Case Analysis, and - HW 2 - Due Monday 7/8 at 11:59PM
Mergesort
Additional reading: AI Part I 1.4, 1.5,
1.6, 2; CLRS 2.3, 3
3 7/8/2024 Solving Recurrences and the Master - HW 3 - Due Monday 7/15 at 11:59PM
Theorem, Median and Selection
(Online Class Through Zoom)
Additional reading: AI Part I 4, 6;
CLRS 4.3, 4.4, 4.5, 9
4 7/15/2024 Randomized Algorithms and QuickSort - HW 4 - Due Monday 7/22 at 11:59PM
BucketSort and Lower Bounds for Sorting
Additional reading: AI Part I 5, 5.6;
CLRS 5.1, 5.2, 5.3, 7, 8.1, 8.2
5 7/22/2024 Binary Search Trees and Red-Black Trees - No weekly homework due Midterm
Additional reading: AI Part II 11; - Remember to repass everything you've seen so far
CLRS 12.1, 12.2, 12.3, 13
6 7/29/2024 Hashing - In-class Midterm - Day Tuesday 7/30 at 06:00PM
Additional reading: AI Part II 12; CLRS 11 - Online-class - Open from 7/30 at 06:00PM to 8/2 at 06:00PM
- HW 5 - Due Monday 8/5 at 11:59PM
7 8/5/2024 Graphs and BFS and DFS, topological sort - HW 6 - Due Monday 8/12 at 11:59PM
Strongly Connected Components
Additional reading: AI Part II 7, 8.1,
8.2, 8.3, 8.4, 8.5, 8.6; CLRS 22.1, 22.2,
22.3, 22.4, 22.5
8 8/12/2024 Dijkstra and Bellman-Ford - HW 7 - Due Monday 8/19 at 11:59PM
Bowling Notes, LCS, LIS, Coins Notes
Additional reading: AI Part II 9,
Part III 18.1, 18.2; CLRS 24.1, 24.3
9 8/19/2024 Dynamic Programming: Bellman-Ford - HW 8 - Due Monday 8/26 at 11:59PM
and Floyd-Warshall
Additional reading: AI Part III 18;
CLRS 25.2, 15.1
10 8/26/2024 Minimum Spanning Trees - No weekly homework due Final Exam
Additional reading: AI Part III 15; CLRS 23
11 9/2/2024 Assignments - Final - Day Tuesday 9/3 at 06:00PM
- Online-class: Day Tuesday 9/3 at 06:00PM

Honor Code

In all cases, it is not permissible for students to enter exam questions into any software, apps, or websites. Accessing resources that directly explain how to answer questions from the actual assignment or exam is a violation of the Honor Code.

Course Policy for Homework

In all cases, it is not permissible for students to enter homework questions into any software, apps, or websites. Accessing resources that directly explain how to answer questions from the actual assignment or exam is a violation of course policy.

University Policies

In addition to the course policies listed on this syllabus, course assignments or course website, the following University policies are in effect:

Appropriate Use of Course Materials

It is important to recognize that some or all of the course materials provided to you are the intellectual property of Drexel University, the course instructor, or others. Use of this intellectual property is governed by Drexel University policies, including the IT-1 policy found at: https://drexel.edu/it/about/policies/policies/01-Acceptable-Use/ Briefly, this policy states that all course materials including recordings provided by the given prior written approval by the University. Doing so may be considered a breach of this policy and will be investigated and addressed as possible academic dishonesty, among other potential violations. Improper use of such materials may also constitute a violation of the University's Code of Conduct found at: https://drexel.edu/cpo/policies/cpo-1/ and will be investigated as such.

Recording of Class Activities:

In general, students and others should not record course interactions and course activities in lecture, lab, studio or recitation. Students who have an approved accommodation from the Office of Disability Resources to record online lectures and discussions for note taking purposes should inform their course instructor(s) of their approved accommodation in advance. The recording of lectures and discussions may only be carried out by the students enrolled in the class who have an approved accommodation from Disability Resources with their instructors' prior knowledge and consent. Students with approved accommodations may be asked to turn off their recorder if confidential or personal information is presented. If a student has any comments, concerns, or questions about provided class materials and/ or recording, talk to your course instructor first. If this does not resolve the issue, you can also reach out to the Department Head, and use the process described for a grade appeal to move your concern forward. The process described for grade appeals can be found at: https://drexel.edu/provost/policies/grade-appeals/

CCI's Commitment to Diversity, Equity, and Inclusion (DEI)

The College of Computing & Informatics commits to creating a positive and safe learning environment for everyone - instructors, professional staff, and students - both inside and outside of the classroom. We embrace the diversity of thoughts, perspectives, and experiences that each community member brings, and we honor everyone's identity (including, but not limited to, race, ethnicity, age, gender, socioeconomic status, sexuality, religion, veteran status, and disability). We encourage each community member to share information regarding pronouns, religious and cultural holidays, accommodations, and any other information that will assist instructors in fostering a supportive and inclusive community environment. For more information about CCI's commitment to DEI, visit Diversity, Equity & Inclusion Council | Drexel CCI.

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