Class Location and Times
Lecture: Hasbrouck 126, MW 2:30-3:45pm (Section 1), 4:00-5:15pm (Section 2)
Discussions: Flint 201, F 9:05am, 10:10am, 12:20pm, 1:25pm (50 min.)
Course Staff
Course Objectives, Prerequisites, and Learning Outcomes
Welome to COMPSCI 311 - Introduction to Algorithms. This course will introduce you to algorithms in a variety of areas of interest, including graph and network algorithms, scheduling, searching, sorting, and string processing. More than just a list of classic algorithms, in this course you will learn and practice algorithm design and problem solving. To implement in code solutions to complex problems, we must first design such algorithms. We will learn how to do this, typically using the following steps:
Learning Management Systems and Communication
We use Moodle to post course material and quizzes, and Gradescope for submission and grading of homework.
We use Campuswire for course communication, including any announcements, see the communication policy below for more details.
We will use ClassQuestion for in-class questions which count towards your grade. Please sign up with your UMass email address.
Resources
Letter grade thresholds (tentative):
90: A
86: A-
82: B+
78: B
74: B-
70: C+
66: C
62: C-
58: D+
54: D
These thresholds may be adjusted based on the overall performance in the course, but will not be more strict.
Attendance and late work submission policy
You are expected to attend lectures -- this is the best way to engage in discussion and understanding of the material. Participation and lecture questions are a part of the course grade. If you cannot attend (e.g., for medical reasons), you are expected to watch the lecture recordings.
Discussion attendance is mandatory and part of the course grade. If you cannot attend a discussion (e.g., for medical reasons), you must notify the TA leading your section ahead of time to determine how to make up the discussion activity.
All homework will be due at 11:59 PM on the due date. You get one late day to use on one homework of your choice and one late day for a challenge set of your choice. Please allow time to check and make sure you've submitted everything properly, and avoid any unexpected issues (slow Internet connection, uploading the wrong file in a hurry, etc.) Also, expect problems to take several iterations of thinking and coming up with the solution, refining, etc., to complete. We suggest you begin working on them early, so you can ask any needed questions, discuss them in your study groups and use office office hours effectively.
Communication policy and response frequency
We use Campuswire for communication. We will attempt to answer all questions within 24 hours and often much sooner. However, you should not rely on last-minute questions for help on homework.
When needed, use private instructor-only posts rather than e-mail, this will make them more readily seen, and any of the staff team can answer them.
For sensitive private matters, email the instructors.
Academic Honesty and Collaboration Policy
You are encouraged to form study groups, learn and discuss the course material jointly with others.
You must do learning assessment quizzes, homework assignments and exams on your own.
You may collaborate with a few other students on challenge problems, provided that (a) you indicate anyone with whom you worked and (b) the final presentation is entirely your own. As a guideline, to distinguish discussion from plagiarism, it is useful to divide work into an "ideas phase", in which you can discuss problems (verbally or perhaps using a whiteboard) but do not leave with shared written matter, and a "writeup phase", which you do entirely on your own. If you have questions about this matter, please ask.
You are encouraged to ask public questions, in office hours or on Campuswire. Your questions and the answers to them can be useful for others as well (and you are encouraged to help with answers). Public questions about homework should be of a general nature (clarification, applicable course material, asking for hints), and not involve details of your solution attempt. Use private questions otherwise if needed.
This course assumes that all work submitted by students will be generated by the students themselves, working individually or in groups. Students should not have another person/entity do the writing of any portion of an assignment for them, which includes hiring a person or a company to write assignments and using artificial intelligence tools like ChatGPT.
As members of the College of Information and Computer Sciences at UMass Amherst we expect everyone to behave responsibly and honorably. In particular, we expect each of you not to give, receive, or use aid in examinations, nor to give, receive, or use unpermitted aid in any academic work. Doing your part in observing this code, and ensuring that others do likewise is essential for having a community of respect, integrity, fairness, and trust.
If you cheat in a course, you are taking away from your own opportunity to learn and develop as a professional. You also hurt your colleagues, and this will hurt people you will work with in the future, who expect an honest and responsible professional.
As faculty, we pledge to use academic policies designed for fairness, avoiding situations that are conducive to violating academic honesty, as well as unreasonable or unusual procedures that assume dishonesty.
We will follow the university's Academic Honesty Policy and Procedures established by the university to ensure that the learning environment is both honest and fair. Integrity is essential in all aspects of higher education, academic dishonesty is prohibited in all university programs, including this course. Academic dishonesty as defined by the University's Academic Honesty Policy includes but is not limited to:
Supplementary student support resources CICS has its own tutoring program, which allows you to get help from students who have taken the course in the past. Submit a request here (usually available starting the second weel of the semester). Tutoring is also provided by the . More student support resources are provided by the CCPH. If you feel you are struggling, do not hesitate to reach out to any of the course staff and we will help you find the best solution.
Accomodations
Both the University of Massachusetts Amherst and your course staff are committed to providing an equal educational opportunity for all students. If you have a physical, psychological, or learning disability documented with Disability Services, please communicate your needs to us in the first two weeks of the semester so that we may make any necessary accommodations. If you are not sure if you qualify for an accommodation or if you have any questions on the topic of accommodations please contact Disability Services for more information.
Equity and Inclusion Statement
We are committed to fostering a culture of diversity and inclusion, where everyone is treated with dignity and respect. This course is for everyone. This course is for you, regardless of your age, background, citizenship, disability, sex, education, ethnicity, family status, gender, gender identity, geographical origin, language, military experience, political views, race, religion, sexual orientation, socioeconomic status, or work experience.
Because of that, we should realize that we will be bringing different skills to the course, and we will all be learning from and with each other. We may have different background and skills in courses taken, mathematical, algorithmic, coding or testing background, ways to communicate orally and in writing, working alone or in groups, or plans for professional careers.
Please be kind and courteous. Respect that people have differences of opinion, and work and approach problems differently. There is seldom a single right answer to complicated questions. Please keep unstructured critique to a minimum; any criticism should be constructive.
Disruptive behavior is not welcome, and insulting, demeaning, or harassing anyone is unacceptable. In particular, we don't tolerate behavior that excludes people in socially marginalized groups. If you feel you have been or are being harassed or made uncomfortable by someone in this class, please contact a member of the course staff immediately, or if you feel uncomfortable doing so, contact the Dean of Students office.
This course is for all of us. We will all learn from each other. Welcome!
Use of chosen names and pronouns
Everyone has the right to be addressed by the name and pronouns that they use for themselves. Students can indicate their preferred/chosen first name and pronouns on SPIRE, which appear on class rosters. Please let me know what name and pronouns I should use for you if they are not on the roster. A student’s chosen name and pronouns are to be respected at all times in the classroom.
Title IX Statement
Title IX of the Education Amendments of 1972 is a federal civil rights law that prohibits discrimination on the basis of sex in any education program or activity that receives federal funding. Sex discrimination includes sexual harassment, sexual battery, sexual assault, and rape. Title IX applies to all public and private educational institutions receiving federal financial assistance.
If you have been the victim of sexual violence, gender discrimination, or sexual harassment, the university can provide you with a variety of support resources and accommodations. UMass is committed to providing these resources with minimal impact and costs to survivors on a case-by-case basis. Resources are available to survivors with or without them filing a complaint. No upfront costs are charged to any currently enrolled students for University Health Services or the Center for Counseling and Psychological Health, and no fees exist for services in the Dean of Students Office, the Center for Women and Community, Student Legal Services, or by live-in residential staff.
Schedule
This is a tentative schedule which might suffer changes. See also the page for Spring 2022.
Lecture | Topics | Readings |
---|---|---|
1 | Introduction and Stable Matching | Chapter 1.1 |
2 | Algorithm Analysis and Asymptotics | Ch 2.1, 2.2 |
3 | Algorithm Analysis, Graphs | Ch 3.1, 3.2 |
4 | Graphs | Ch 3.3, 3.4 |
5 | Graphs | Ch 3.5, 3.6 |
6 | Greedy Algorithms | Ch 4.1 |
7 | Greedy Algorithms | Ch 4.2, 4.3 |
8 | Greedy Algorithms | Ch. 4.4 |
9 | Greedy Algorithms | Ch. 4.5, 4.6 |
10 | Divide and Conquer | Ch. 5.1, 5.2 |
11 | Divide and Conquer | Ch. 5.2, 5.3 |
12 | Divide and Conquer | Ch. 5.4, 5.5 |
13 | Dynamic Programming | Ch. 6.1, 6.2 |
14 | Dynamic Programming | Ch. 6.3, 6.4 |
15 | Dynamic Programming | Ch. 6.6 |
16 | Dynamic Programming | Ch. 6.8 |
17 | Network Flow | Ch. 7.1, 7.2 |
18 | Network Flow | Ch. 7.2, 7.3 |
19 | Network Flow | Ch. 7.5 |
20 | Intractability | Ch. 8.1 |
21 | Intractability | Ch. 8.2, 8.3 |
22 | Intractability | Ch 8.3 |
23 | Intractability | Ch 8.4 |
24 | Approximation Algorithms | Ch 11.1, 11.2 |
25 | Randomized Algorithms | Ch 13.1, 13.2, 13.4 |
26 | Approximation/Randomization/Review |