Engineering tomorrow's software solutions.

Cornell's software engineering researchers develop innovative approaches to improve software quality and developer productivity. The team creates new automated techniques and tools for testing, verification, and quality assurance, with particular emphasis on machine learning systems and lightweight formal methods. Their work combines rigorous technical innovation with practical solutions derived from studying real developer needs.

Key research areas include software testing methodologies, quality assurance for ML systems, runtime verification, and developer-friendly formal methods. This technical foundation supports broader impacts in software engineering education and industry practice.

Faculty studying software engineering.

A black and white photo of Kenneth Birman, a man with glasses wearing a suit and tie.
Ken Birman
N. Rama Rao Professor of Computer Science
Ken Birman
N. Rama Rao Professor of Computer Science
Contact
(607) 227-0894
ken@cs.cornell.edu
Birman's Website
A photo of Saikat Dutta, a man with dark brown hair and a beard, wearing a blue shirt in front of a leafy background
Saikat Dutta
Assistant Professor of Computer Science
Saikat Dutta
Assistant Professor of Computer Science
Contact
saikatd@cornell.edu
Dutta's Website
A photo of Sainyam Galhotra, a man with a shaved head, a dark beard, dark glasses and a blue shirt in front of a leafy background.
Sainyam Galhotra
Assistant Professor of Computer Science
Sainyam Galhotra
Assistant Professor of Computer Science
Contact
sg@cs.cornell.edu
Galhotra's Website
A photo of Owolabi Legunsen, a man with short black hair and mustache, in a black sweater in front of a gold background
Owolabi Legunsen
Assistant Professor of Computer Science
Owolabi Legunsen
Assistant Professor of Computer Science
Contact
(607) 216-4264
legunsen@cornell.edu
Legunsen's Website
A photo of Fred Schneider, a man with dark gray hair and a mustache, in a striped shirt in front of a staircase
Fred B. Schneider
Samuel B. Eckert Professor of Computer Science
Fred B. Schneider
Samuel B. Eckert Professor of Computer Science
Contact
(607) 255-9221
fbs@cs.cornell.edu
Schneider's Website
A photo of Alexandra Silva, a smiling woman with shoulder length brown hair and a blue shirt in front of a gray background
Alexandra Silva
Professor of Computer Science
Alexandra Silva
Professor of Computer Science
Contact
alexandra.silva@cornell.edu
Silva's Website
  • ISSTA 2024. An In-depth Study of Runtime Verification Overheads during Software Testing. Kevin Guan and Owolabi Legunsen.
  • ICSE 2023. Balancing Effectiveness and Flakiness of Non-Deterministic Machine Learning Tests. Steven Xia, Saikat Dutta, Sasa Misailovic, Darko Marinov, and Lingming Zhang.
  • Computing in Science & Engineering 2023. Curran D. Muhlberger. Challenges and Techniques for Reproducible Simulations.
  • UAI 2023. ASTRA: Understanding the Practical Impact of Robustness for Probabilistic Programs. Zixin Huang, Saikat Dutta, and Sasa Misailovic.
  • SOSP 2023. Acto: Automatic End-to-End Testing for Operation Correctness of Cloud System Management. Jiawei Tyler Gu, Xudong Sun, Yuxuan Jiang, Chen Wang, Mandana Vaziri, Owolabi Legunsen, and Tianyin Xu.
  • ISSTA 2023. More Precise Regression Test Selection via Reasoning about Semantics-Modifying Changes. Yu Liu, Jiyang Zhang, Pengyu Nie, Milos Gligoric, and Owolabi Legunsen.
  • RV 2023. eMOP: A Maven Plugin for Evolution-Aware Runtime Verification. Ayaka Yorihiro, Pengyue Jiang, Valeria Marques, Benjamin Carleton, and Owolabi Legunsen.
  • ISSTA 2023. Extracting Inline Tests from Unit Tests. Yu Liu, Pengyu Nie, Ana Guo, Milos Gligoric, and Owolabi Legunsen.
  • TSE 2023. Runtime Verification of Crypto APIs: An Empirical Study. Adriano Torres, Pedro Costa, Luis Amaral, Jonata Pastro, Rodrigo Bonifácio, Marcelo d’Amorim, Owolabi Legunsen, Eric Bodden, and Edna Dias Canedo.
  • ASE 2022. Inline Tests. Yu Liu, Pengyu Nie, Owolabi Legunsen, and Milos Gligoric.