Academic Integrity

For more details, please see the department policy on academic integrity .

Withdrawing a submission for academic integrity violation

Sometimes mistakes can happen so you have the option of withdrawing any of your Homework submission within 24 HOURS of the assignment deadline. You can do this by sending Prof. Carlson or Prof. Luo an email, e.g. by using the following template (thanks to Oliver Kennedy for providing us the template):

On receiving the above email, we will assign J a 0 on Question X on Homework/Assignment N but disregard any Academic Integrity issues with the problematic submission. Note that J is not required to present any details on how they violated academic integrity.

Accessibility Resources

If you have a diagnosed disability (physical, learning, or psychological) that will make it difficult for you to carry out the course work as outlined, or that requires accommodations such as recruiting note-takers, readers, or extended time on exams or assignments, you must consult with Accessibility Resources (: 60 Capen Hall, : 716-645-2608 (phone), : 716-645-3116 (fax)).

You must advise your instructor during the first two weeks of the course so that we may review possible arrangements for reasonable accommodations.

Instructor Information

Course Staff

Course Staff: TBA.

Contacting Course Staff

Course announcements and class discussion will use Piazza. The link to Piazza will be available on UBLearns. Please use the course communication channels announced on UBLearns to contact the instructional staff.

Lectures

You are expected to attend class and are responsible for the material discussed in the current semester.

You may attend a lecture other than the one for which you are registered if there is space and doing so does not create a burden for the instructor.

Recitations

A1: Wednesday, 3:00–3:50 PM — Bell 337
A4: Wednesday, 5:00–5:50 PM — O'Brian 214
B1: Monday, 12:00–12:50 PM — Talbert 111
B2: Monday, 1:00–1:50 PM — Clemens 215
B3: Monday, 3:00–3:50 PM — Capen 108

Recitations provide an opportunity to review course material, work through problems, and ask questions in a smaller setting.

You may attend a recitation other than the one for which you are registered if there is space and doing so does not create a burden for the instructor or course staff.

Course Description

(From the course catalog )

Introduces paradigms for designing algorithms and fundamental limitations to what algorithms can do. Covers basic algorithm design paradigms of greedy algorithms, divide and conquer algorithms and dynamic programming, as well as a selection of advanced algorithmic topics, such as randomized algorithms, algorithms for distributed systems and basic algorithms for machine learning. Topics related to limitations of algorithms include NP-completeness and undecidability. Coverage includes analyzing algorithms via proofs and programming assignments to implement algorithms.

Ethical considerations of algorithms

Algorithms are increasingly pervasive in our daily lives. They are increasingly used in all aspects of society, from benign applications of recommending movies to more impactful application of determining sentencing in criminal justice systems. While most of us are in CSE because we like to build technology, given the pervasive nature to CSE, it is imperative for you to understand the societal and ethical implications of the algorithms and technology that you build. This is not to say that you necessarily have to be an activist looking out for societal implications of algorithms, but you should be aware that the algorithms you design will have real-life implications and that saying "you just designed the algorithm and cannot be responsible for how it is used" is, at best, a weak excuse. When developing algorithms (and the corresponding system) you will have to choose between many options. Being aware of the downstream ethical and societal implications would help you make better choices when designing your technology.

Thus, in this course, in addition to learning the technical fundamentals of algorithms (which are of course still very important), you will also look into societal implications in general and ethical implications of algorithms in real life. In particular, we will focus on how uses of algorithms affects real life. So e.g., we will be more interested in situations where algorithmic prediction of recidivism in criminal justice is biased and not e.g. ethical issues involved in stealing of algorithms and intellectual property rights.

You will work on ethical and societal implications of algorithms primarily in your Project.

Prerequisites and Credits

Data Structures (CSE 250), [Discrete Math (CSE 191) OR Intro to Higher Math (MTH 311)] and College Calculus II (MTH 142 or MTH 139). Ideally, you should have a grade of $C^-$ or above in these courses. If you do not satisfy this requirement, please come and see us.

This is a $4$ credit course.

(ABET ) Learning Outcomes

This course is required of all computer science students and after the completion of the course, students should demonstrate mastery of the concepts/skills/knowledge expressed in the following learning outcomes for computer science:

• (4) recognize professional responsibilities and make informed judgments in computing practice based on legal and ethical principles.
• (5) Function effectively as a member or leader of a team engaged in activities appropriate to the program’s discipline.
• (6) Apply computer science theory and software development fundamentals to produce computing-based solutions. [CS]

Course Learning Outcome	Program Outcomes / Competencies	Instructional Method(s)	Assessment Method(s)
Be able to design algorithms to solve given problems	ABET (6)	Lectures	Homeworks, Exams
Be able to prove correctness of designed algorithms	ABET (6)	Lectures	Homeworks, Exams
Be able to identify ethical and societal implications of algorithms	ABET (4)	Lectures	Project
Be able to effectively work in a team	ABET (5)	Lectures	Project

The Student Outcomes from the Computing Accreditation Commission (CAC) of ABET have been adopted .

Program Outcome Support (Computer Science ABET Outcomes):

Program Outcome	1	2	3	4	5	6
Support Level	No coverage	No coverage	No coverage	Demonstrate mastery of skill/concept	Demonstrate mastery of skill/concept	Demonstrate mastery of skill/concept

References

We will be using the following textbook:

Occasionally, we might study topics that are not covered in the textbook. In such cases, supplementary material will be provided.

The following textbooks could be useful references:

• Thomas S. Cormen, Charles E. Leiserson, Ronald Rivest, and Clifford Stein, "Introduction to Algorithms (2nd Ed) ." MIT Press, 2001.
• Sanjoy Dasgupta, Christos H. Papadimitriou and Umesh Vazirani, "Algorithms ." McGraw Hill, 2007.
• Donald Knuth, "The Art of Computer Programming Volumes 1, 2, 3, 4 ." Addison Wesley.
• Alfred V. Aho John E. Hopcroft and Jeffrey Ullman, "Data Structures and Algorithms ." Addison Wesley, 1983.
• Richard E. Neapolitan, "Foundations of Algorithms (5e) ." Jones and Bartlett, 2015.
• Daniel J. Velleman, "How to Prove It: A Structured Approach (2nd Ed) ." Cambridge University Press, 2006.

However, note that for your homework submissions, the Kleinberg-Tardos book is the only allowed source. Please see the homework policy for more details.

Schedule

The course follows a 16-week academic calendar. Topics include stable matching and algorithm analysis; graphs and graph traversal; greedy algorithms; divide and conquer; dynamic programming; and computational complexity and reductions. We will also briefly discuss undecidability early in the semester.

See the detailed course schedule for lecture topics, assignments, recitations, quizzes, and exam dates.

Piazza

We will use Piazza for course announcements and class discussion. The link to the course Piazza will be available on UBLearns. Students are expected to check course announcements regularly.

Grading Policy

Your final course grade will be calculated using the following weights:

Component	Weight
Project	10%
Homeworks	25%
Quizzes	5%
Midterm I	15%
Midterm II	15%
Final Exam	30%

Project

Group Score

As part of your project, you will also work in a group to complete a series of programming tasks and then reflect on your design choices (as well as the project). These will contribute to the group score part of the project, which is worth $5\%$ of your grade (which is divided into the coding component and the reflection component).

Coding Component

As mentioned earlier, as part of your project you will work in a group to complete a series of programming tasks. All of these tasks will be based on one real-life case study. Unlike the programming questions on the homework, the coding mini project will have you solve problems for which there is no provable optimal solution and where you will have to balance multiple goals. More importantly, you will have to deal with some ethical and societal issues (see reflection component of the project).

For more details, please see the project page.

Reflection Component

As part of your project, in addition to completing a series of programming tasks, your group will reflect on ethical and societal considerations of your coding assignments (and more generally the project).

For more details, please see the project page.

Individual Component

At the end of the project, you will rate your own and your other group members' contributions to the project. For more details, please see the project page.

The project will assess student outcomes (4) and (5).

Homeworks

Homework assignments will be released on Wednesdays according to the course schedule and will be due on the Wednesday indicated on the schedule. Homework 0 will be graded for feedback but will not count toward the final course grade.

For more details, including information about circumstances that may result in a letter-grade reduction in the course, please see the homework policy document. The line between collaboration and cheating can be blurry; when in doubt, play it safe. The homework is designed around work that we believe is important for you to do yourself rather than busy work. The course generative-AI policy therefore applies to homework submissions.

All homework assignments assess student learning outcome (6).

Quizzes

There will be 12 quizzes during the semester. Some weeks will not have a quiz. Quizzes will be taken on UBLearns and will be announced in class. The first quiz will cover the course website and syllabus.

The quizzes will assess student learning outcome (6).

Exams

There will be two in-class midterms and a final exam.

• Midterm I: Friday, October 2 — 15% of the final course grade.
• Midterm II: Friday, October 30 — 15% of the final course grade.
• Final Exam: Wednesday, December 9 — 30% of the final course grade.
• Section A Final Exam Time and Location: 8:00 AM - 11:00 AM, Obrian 104
• Section B Final Exam Time and Location: 3:30 PM - 6:30 PM, Clemen 120

Each midterm will take place during the regular class meeting. For each midterm and the final exam, you may bring one 8.5 × 11 inch sheet of paper and may use both sides.

Study Time

In this course, as in any course, you are expected to put in additional time beyond the scheduled class times. Professors generally expect that for each credit hour a typical student will put in 2–3 hours of time each week outside of class. Since this is a 4-credit course that translates into 8–12 hours of time outside of scheduled times, each week. During this time you should review your lecture notes, attend office hours as needed, and work on assignments. As a rough guide, you should expect to spend at least the following time working on this course, each week:

Lectures	3 hours
Recitation	1 hour
Individual/group study	2 hours
Assignments	6 hours

Miscellaneous Notes

Here are some other policies/suggestions to keep in mind:

1. Your grade

   Your grade will solely depend on your performance in this semester: you will not get any opportunity to do extra work to improve your grade. It is your responsibility to make sure you understand what is expected of you. This course will require a fair bit of work so if you are busy this semester, please plan accordingly.

2. If there is a genuine reason for re-grading, please contact the person who graded your homework/exam within a week of when the graded material is handed back.
3. See advice from CSE 331 TAs on how to do well in this course.
4. If you are not super comfortable with proofs then you will need to put in some extra work to do well in class. The important thing to remember in this case is that you are not good at algorithms yet:
5. Feel free to make up a group of three students and stick with it for all your homeworks and the mini project. You can also use the group as your study group for the course. Piazza offers a mechanism to search for groupmates.

Critical Campus Resources

Sexual Violence

UB is committed to providing a safe learning environment free of all forms of discrimination and sexual harassment, including sexual assault, domestic and dating violence and stalking. If you have experienced gender-based violence (intimate partner violence, attempted or completed sexual assault, harassment, coercion, stalking, etc.), UB has resources to help. This includes academic accommodations, health and counseling services, housing accommodations, helping with legal protective orders, and assistance with reporting the incident to police or other UB officials if you so choose. Please contact UB’s Title IX Coordinator at 716-645-2266 (phone) for more information. For confidential assistance, you may also contact a Crisis Services Campus Advocate at 716-796-4399 (phone).

Mental Health

As a student you may experience a range of issues that can cause barriers to learning or reduce your ability to participate in daily activities. These might include strained relationships, anxiety, high levels of stress, alcohol/drug problems, feeling down, health concerns, or unwanted sexual experiences. Counseling, Health Services, and Health Promotion are here to help with these or other issues you may experience. You can learn more about these programs and services by contacting:

Counseling Services

120 Richmond Quad (North Campus), 716-645-2720 (phone)

Health Services

4350 Maple Road (at Sweet Home Rd.) , 716-829-3316 (phone)

Health Promotion

114 Student Union (North Campus), 716-645-2837 (phone)

Preferred Name

If you would like to be addressed by a name that is different from the one in UB records, please let us know and we will use your preferred name in our communications with you. Furthermore, you will be able to use your preferred name in all of your exams and quizzes (the homeworks will be submitted online so this issue should not come up there).

Diversity

The UB School of Engineering and Applied Sciences considers the diversity of its students, faculty, and staff to be a strength, critical to our success. We are committed to providing a safe space and a culture of mutual respect and inclusiveness for all. We believe a community of faculty, students, and staff who bring diverse life experiences and perspectives leads to a superior working environment, and we welcome differences in race, ethnicity, gender, age, religion, language, intellectual and physical ability, sexual orientation, gender identity, socioeconomic status, and veteran status.

Suggestions or Comments?

we would be happy to get feedback from you. You can either talk/send email to us, or use Piazza.