Time/Location
Tuesday/Thursday 10:30am–11:50am, Catskill 130
Instructor
Amir Masoumzadeh (amasoumzadeh@albany.edu)
  • Office Hours: Tuesday/Thursday 4pm–5pm, or by appointment (Zoom link on Blackboard)
Teaching Assistant
Josue Ruiz (jaruiz@albany.edu)
  • Office Hours: Wednesday 10am–11am (UAB 412F or Zoom link on Blackboard), Friday 10am–11am (Zoom link on Blackboard)

Course Overview

This is a graduate-level course on data structures and algorithms with an emphasis on algorithm design techniques and analysis of algorithms. Students will learn about design techniques such as divide-and-conquer, dynamic programming, greedy, and approximation. They will also learn about proving the correctness of algorithms, complexity analysis of algorithms, and complexity theory. Advanced algorithms and data structures in different areas such as trees and graphs will be explored.

Prerequisites

Students are expected to have previously taken an undergraduate level course on data structures and algorithms. Therefore, they are expected to know about basic data structures (such as lists, heaps, and binary search trees), and basic algorithms (such as sorting and searching).

Textbook

Introduction to Algorithms (3rd Edition) By Cormen, Leiserson, Rivest, and Stein (ISBN: 9780262033848) (Required Reading)

Optional Readings:

Communication and Submissions

The course syllabus and schedule is available on the course webpage. Most of the tasks in this class will be handled via Blackboard including distribution of lecture notes, homework assignments, feedback, and grades.

Assessment and Grading

The course is A-E graded based on the following categories and corresponding weights. Conversion from the final numerical grade to the letter grade is based on cutoffs determined according to the grade distribution in the class. This results in more flexible and favorable grades compared to using a fixed conversion scale.

Participation and In-Class Activities (5%)
Homework Assignments (45%)
There will be about 6 problem sets. Your lowest grade will be dropped.
Exams (50%)
There will be a midterm exam (taken during regular class sessions) and a final exam. Each exam is worth 25% of your total grade.

Schedule

The following schedule is tentative and will be regularly updated. It is your responsibility to check the schedule regularly.

Date Topic/Reading Assignment
Jan25 Course Overview, Introduction to Algorithms
  • Chapter 1
Jan27 Analyzing algorithms
  • Chapter 2
Feb01 Asymptotic Notation
  • Chapters 3
Feb03 Divide-and-Conquer
  • Chapters 2, 4
Homework 1 due Feb11
Feb08 Divide-and-Conquer (cont.)
  • Chapter 4
Feb10 Probabilistic Analysis
  • Chapter 5
Feb15 Randomized Algorithms
  • Chapters 5
Feb17 Amortized Analysis
  • Chapter 17
Homework 2 due Feb25
Feb22 Amortized Analysis (cont.), Dynamic Programming
  • Chapters 17, 15
Feb24 Dynamic Programming (cont.)
  • Chapter 15
Mar01 Dynamic Programming (cont.)
  • Chapter 15
Homework 3 due Mar07
Mar03 Greedy Algorithms
  • Chapter 16
Mar08 Midterm Review
Mar10 Midterm Exam
Mar15 No Class (Break)
Mar17 No Class (Break)
Mar22 Graph Representation and Basic Algorithms
  • Chapter 22
Mar24 Graph Representation and Basic Algorithms (cont.)
  • Chapter 22
Mar29 Graph Representation and Basic Algorithms (cont.)
  • Chapter 22
Homework 4 due Apr05
Mar31 Minimum Spanning Trees
  • Chapter 23
Apr05 Shortest Paths
  • Chapters 24, 25
Apr07 Shortest Paths (cont.)
  • Chapters 24, 25
Apr12 Shortest Paths (cont.)
  • Chapters 24, 25
Homework 5 due Apr19
Apr14 Maximum Flow
  • Chapter 26
Apr19 Maximum Flow (cont.)
  • Chapter 26
Apr21 Maximum Flow (cont.)
  • Chapter 26
Homework 6 due May02
Apr26 NP-Completeness
  • Chapter 34
Apr28 NP-Completeness (cont.)
  • Chapter 34
May03 Final Review
May10 (Tue) Final Exam (8am-10am)

Policies

No Late Submission
Assignments will be released at least a week before their due date. You are highly recommended to study an assignment as soon as it becomes available. There will be ample opportunities to benefit from office hours and communication with me and the TAs before the due date. Assignments are due 11:59pm on the day of their deadline. Submissions after due time will receive no points.
Review of Grades
Any issue regarding your grade in a specific assignment must be communicated to us no later than 5 business days after the posting day of the grades. There will be no re-grading after the 5-day period has passed.
Attending Exams
The midterm exam is given in regular hours of the class. The final exam will be during the final exam period. Tentative exam dates are given in the course schedule, and there will be usually reminders about them in the lectures. Makeup exams will be given only for valid and verifiable extenuating circumstances (e.g., a major medical situation). It is the student’s responsibility to contact the instructor at least a week ahead of the exam date and arrange to take a makeup exam at an alternate date/time. Makeup exams are not guaranteed and will be generally harder than the regular exams.
Academic Integrity
It is every student’s responsibility to become familiar with the standards of academic integrity at the University. Claims of ignorance, of unintentional error, or of academic or personal pressures are not sufficient reasons for violations of academic integrity. Any incident of academic dishonesty can result in (i) no credit for the affected assignment, (ii) report to the appropriate University authorities (e.g., Dean of Undergraduate Education or Graduate Studies), and/or (iii) a failing grade for the course.

For all assignments and papers, you must submit your own work, except where collaboration is explicitly permitted or required. Also, you must properly cite any resources from which you borrow ideas and clearly distinguish them from your contributions.

Use of Electronic Devices
Computers or other electronic devices may be only used during class for note-taking, in-class exercises, or other class-related activities. You are not allowed to perform any unrelated tasks during class.
Students with Disabilities
Reasonable accommodation will be provided for students with documented disabilities. If you believe you have a disability requiring accommodation in this class, please notify the Disability Resource Center (Campus Center 130, 518-442-5490). That office will provide me with verification of your disability, and will recommend appropriate accommodations. In general, it is your responsibility to contact me at least one week before the relevant activity to make arrangements.
Mental Health
As a student, there may be times when personal stressors interfere with your academic performance and/or negatively impact your daily life. The University at Albany Counseling and Psychological Services (CAPS) provides free, confidential services including individual and group psychological counseling and evaluation for emotional, social, and academic concerns. Given the COVID pandemic, students may consult with CAPS staff remotely by telephone, email, or Zoom appointments regarding issues that impact them or someone they care about. For questions or to make an appointment, call (518) 442-5800 or email consultation@albany.edu. Visit https://www.albany.edu/caps/ for hours of operation and additional information.

If your life or someone else’s life is in danger, please call 911. If you are in a crisis and need help right away, please call the National Suicide Prevention Lifeline at 1-800-273-TALK (8255). Students dealing with heightened feelings of sadness or hopelessness, increased anxiety, or thoughts of suicide may also text “GOT5” to 741741 (Crisis Text Line).

Mask Mandate
The university health and safety protocols including face mask guidelines will be strictly followed. All students must wear masks while inside any campus building, including inside classrooms. Students not wearing a mask in class will be asked to leave. Students who forgot a mask may obtain one at the Campus Center Help Desk and the Academic Support Center in LI36. See the university’s basic safety protocols.