CS 5150: Software Engineering (Spring 2026)

Syllabus

Course description

Introduction to the practical problems of specifying, designing, building, testing, deploying, and maintaining reliable software systems. Emphasis on team-based development integrating with moderately large, existing systems. Topics include design patterns, issue tracking, version control, code review, dependency management, continuous integration, and release management. As a central part of the course, student teams will add large features to real software systems, following an agile development process.

Prerequisites

Minimum: CS 2110 or equivalent experience programming in Java or C++. CS 3110 or CS 4410/4414 strongly recommended for Cornell undergraduates. Sufficient maturity to design, code, and debug large programs and to learn new programming languages and tools.

Instructor

Saikat Dutta
Lecturer, Computer Science
Gates Hall 438
saikatd@cornell.edu
Office Hours: Mondays 1 PM - 2 PM, Gates 438 or by Appointment

Teaching Assistants

Joonhwan Yoo
jy345@cornell.edu
Stephen Shen
zs435@cornell.edu
Junkai Huang
jh2973@cornell.edu
Kabir Anirudh Samsi
kas499@cornell.edu
Harsh Patel
hhp26@cornell.edu
Kaityln Lu
kl995@cornell.edu

TA Office Hours: Wednesdays 1-2 PM; Room: TBD

Meeting times

Lectures are held Tuesdays and Thursdays from 1:25pm to 2:40pm, beginning on January 20 and ending on May 5. Attendance and participation are expected. In-person lectures take place in Gates G01 (see Class Roster).

Project Teams will need to arrange meeting times outside of class to conduct reviews with all members in attendance.

Personal technology

Engagement during lectures will be facilitated with Poll Everywhere polls. Responding to polls requires an Internet-connected mobile device (laptop, tablet, or smartphone). However, multitasking on such devices during lecture is known to impede learning and lower grades for both you and your neighbors, so we ask that you only use these devices for poll responses, notetaking, and following along with demos. Students who are nevertheless prone to multitask should sit in the back of the classroom (and classmates should not hesitate to ask distracting students to relocate there).

Materials & services

At a minimum, students will require the following in order to participate in the course:

Students are not required to purchase a textbook; all required readings will be available for free in digital form. Several readings will be from the book Software Engineering at Google, which is also available in paperback.

The course will utilize the following online services, most of which you can access with your Cornell account once you are logged into Canvas:

Assessment/Grading

Performance on the following elements will factor into a student’s course grade:

These components are weighted at the discretion of the instructor, but performance on the group project (that is, consistent application of the techniques taught in class towards a viable, best-effort deliverable) is the most significant factor.

Exams: This class will not have a centrally-scheduled prelim or final; all exams will be given in class. There will be two in-class exams, weighted equally.

Project Scoring Rubrics: These are the high-level components that will be evaluated to determine your project grade. These components are weighted at the discretion of the instructor (but assume equal weightage unless otherwise specified).

Grade Breakdown

Grade Boundaries: The actual grade boundaries have not been decided yet because there are many moving components in the course and they change every year. However, to manage your expectations, we can guarantee that: Scores above 90% will receive at least A-, Scores above 80% will receive at least B-, and scores above 65% will receive at least C-.

Communication

The primary mode of communication for this course will be via Canvas. The course website contains the most up-to-date information about the schedule. We will use Ed for discussions. We will use Gradescope and CMSX for assignments and grading. For any special circumstances, please contact the course staff via email.

AI usage

You may use AI tools to assist with coding, but you must clearly disclose any AI-generated content in your report and ensure that all submitted work meets the course's academic integrity standards. You may not use AI tools for any in-class exams or in-class activities unless explicitly permitted by the instructor. If you have any questions or concerns, please contact the course staff.

Late Assignment

For each assignment or report, students can submit after the due date. Each late day will be penalized by a maximum of 10% per day (at the discretion of course staff). Longer grace periods without penalty for assignments/reports are subject to approval by the instructor and will only be allowed due to any extenuating/extreme, unavoidable circumstances. Late submission for final project report is not allowed.

Attendance

Engaging in classroom activities both improves your learning and creates a more vibrant learning environment for your peers, so we want to reward you for it. Class participation will largely be assessed via Poll Everywhere responses. Students do not need perfect attendance or perfectly correct responses to maximize the participation component of their grade! (Such a policy creates perverse incentives, such as rewarding coming to class when ill, which we do not want.) Please do not contact the staff asking to be excused for an absence – we trust you to manage your health and commitments wisely and will not penalize you for missing class occasionally. If habitual absence causes you to miss more than a third of lectures, that is when you should seek advice from the staff.

Unless the university mandates a move to virtual instruction (such as for the first two weeks of the semester), lectures are offered exclusively in person and are not recorded. But be mindful of public health – if you do not feel well, please stay home. Posted materials, our discussion board, and your teammates are all available to help you get caught up after an absence.

Community of learning and professionalism

We aim to create an inclusive learning environment where diversity and individual differences are respected and appreciated, and we expect students in this class to demonstrate diligence in understanding how others’ perspectives may be different from their own. Behaviors that contribute positively to our community of learning include:

Accommodations

We provide accommodations for disabilities. Students with disabilities can contact Student Disability Services at 607-254-4545 or the instructor for a confidential discussion of their individual needs. If you experience personal or academic stress or need to talk to someone who can help, contact the instructor or:

Academic integrity

Integrity is a cornerstone of both our learning community and professional life. Much of the work in this course is collaborative, but all documents and code submitted must be written solely by the student or team members submitting it, and ideas or feedback from others must be properly attributed. Always abide by Cornell’s Code of Academic Integrity and any course-specific rules regarding its interpretation.