Rangeet Pan

Senior Research Scientist · IBM T.J. Watson Research Center

My research is in software engineering, with a focus on program analysis and the application of large language models to code-related tasks — including code translation, test generation, and application modernization. I received my Ph.D. from Iowa State University.

For the latest updates, see my IBM Research profile.

Google Scholar GitHub LinkedIn Twitter / X Curriculum Vitae

About

Rangeet Pan is a Senior Research Scientist at the IBM T.J. Watson Research Center, Yorktown Heights, NY. His research interests span software engineering, program analysis, and large language models (LLMs).

At IBM Research, his work centers on incorporating program analysis with LLMs for code-to-code tasks: code translation, automated test generation, and application modernization. His test generation work is part of IBM's watsonx Coding Assistant product. He also developed CLDK, an open-source Python library for contextualizing code LLMs with program analysis insights.

He received his Ph.D. in Computer Science from Iowa State University (2022). He holds an M.S. in Computer and Systems Engineering from the University of Houston (2018).

Awards & Recognition

2025 ACM SIGSOFT Distinguished Paper Award — ICSE 2025, Ottawa, Canada
2024 Pat Goldberg Award (Honorable Mention) — IBM Research
2021 Research Excellence Award — Iowa State University
2020 ACM SIGSOFT Distinguished Paper Award — ESEC/FSE 2020
2020 2nd Place, ACM Student Research Competition — ICSE 2020
2020 Robert Stewart Early Research Recognition Award — Iowa State University
2019 ACM Travel Award — ESEC/FSE 2019, Tallinn, Estonia
2017 Merit Scholarship, Phi Beta Delta — University of Houston

Publications

2026

SAINT: Service-level Integration Test Generation with Program Analysis and LLM-based Agents

Rangeet Pan, Raju Pavuluri, Ruikai Huang, Rahul Krishna, Tyler Stennett, Alessandro Orso, and Saurabh Sinha

ICSE 2026 — IEEE/ACM 48th International Conference on Software Engineering
Hamster: A Large-Scale Study and Characterization of Developer-Written Tests

Rangeet Pan, Tyler Stennett, Raju Pavuluri, Nate Levin, Alessandro Orso, and Saurabh Sinha

ICSE-SEIP 2026 — Software Engineering in Practice
Sakura: An Approach for Generating Complex Tests from Natural Language Test Descriptions

Tyler Stennett, Rangeet Pan, Bridget McGinn, Alessandro Orso, and Saurabh Sinha

ISSTA, 2026

2025

ASTER: Natural and Multi-language Unit Test Generation with LLMs

Rangeet Pan, Myeongsoo Kim, Rahul Krishna, Raju Pavuluri, and Saurabh Sinha

ICSE-SEIP 2025ACM SIGSOFT Distinguished Paper

Paper / Blog
AlphaTrans: A Neuro-Symbolic Compositional Approach for Repository-Level Code Translation and Validation

Ali Reza Ibrahimzada, Kaiyao Ke, Mrigank Pawagi, Muhammad Salman Abid, Rangeet Pan, Saurabh Sinha, and Reyhaneh Jabbarvand

FSE 2025 — Proceedings of the ACM on Software Engineering

PDF
Codellm-Devkit: A Framework for Contextualizing Code LLMs with Program Analysis Insights

Rahul Krishna, Rangeet Pan, Saurabh Sinha, Srikanth Tamilselvam, Raju Pavuluri, and Maja Vukovic

ASE 2025 — ACM International Conference on the Foundations of Software Engineering

PDF
Codellm-Devkit: A Framework for Contextualizing Code LLMs with Program Analysis Insights — Tool Demo

Rahul Krishna, Rangeet Pan, Raju Pavuluri, Maja Vukovic, and Saurabh Sinha

ICSE 2025 — Demo Track

GitHub
Otter: Generating Tests from Issues to Validate SWE Patches

Toufique Ahmed, Jatin Ganhotra, Rangeet Pan, Avraham Shinnar, Saurabh Sinha, and Martin Hirzel

ICLR 2025 — Forty-second International Conference on Machine Learning

PDF

2024

Lost in Translation: A Study of Bugs Introduced by Large Language Models while Translating Code

Rangeet Pan, Ali Reza Ibrahimzada, Rahul Krishna, Divya Sankar, Lambert Pouguem Wassi, Michele Merler, Boris Sobolev, Raju Pavuluri, Saurabh Sinha, and Reyhaneh Jabbarvand

ICSE 2024

ACM DL

2023

Towards Supporting Universal Static Analysis using WALA

Rangeet Pan, Rahul Krishna, Divya Sankar, Saurabh Sinha, Julian Dolby, and Raju Pavuluri

PLDI Tutorial 2023
Decomposing a Recurrent Neural Network into Modules for Enabling Reusability and Replacement

Sayem Imtiaz, Fraol Batole, Astha Singh, Rangeet Pan, Breno Dantas Cruz, and Hridesh Rajan

ICSE 2023

2022

Decomposing Convolutional Neural Networks into Reusable and Replaceable Modules

Rangeet Pan and Hridesh Rajan

ICSE 2022
Manas: Mining Software Repositories to Assist AutoML

Giang Nguyen, Md Johirul Islam, Rangeet Pan, and Hridesh Rajan

ICSE 2022

2021

Can Program Synthesis be Used to Learn Merge Conflict Resolutions? An Empirical Analysis

Rangeet Pan, Vu Le, Nachiappan Nagappan, Sumit Gulwani, Shuvendu Lahiri, and Mike Kaufman

ICSE 2021

Pre-print Video MSR Blog

2020

On Decomposing a Deep Neural Network into Modules

Rangeet Pan and Hridesh Rajan

ESEC/FSE 2020ACM SIGSOFT Distinguished Paper

ACM DL
Does Fixing Bug Increase Robustness in Deep Learning?

Rangeet Pan

ICSE SRC 2020 · 2nd Place, Student Research Competition

ACM DL
Repairing Deep Neural Networks: Fix Patterns and Challenges

Md Johirul Islam, Rangeet Pan, and Hridesh Rajan

ICSE 2020

ACM DL

2019

A Comprehensive Study on Deep Learning Bug Characteristics

Md Johirul Islam, Giang Nguyen, Rangeet Pan, and Hridesh Rajan

ESEC/FSE 2019

ACM DL
Static Deep Neural Network Analysis for Robustness

Rangeet Pan

ESEC/FSE SRC 2019

ACM DL

Professional Service

Program Committee Member, FSE Research Track, 2027
Program Committee Member, ICSE Research Track, 2026
Co-Chair, ReCode Workshop, ICSE 2026
Program Committee Member, ICSE NIER Track, 2026
Program Committee Member, ICSE Research Track, 2025
Program Committee Member, ICSE SEIP Track, 2024
Program Committee Member, ASE Research Track, 2024
Program Committee Member, ESEC/FSE Research Track, 2023
Program Committee Member, OOPSLA Artifact Track, 2021
Shadow Program Committee Member, MSR 2021
Web Chair & Organizing Committee, SPLASH 2020 & 2021
External Reviewer, IEEE Transactions on Software Engineering (TSE)
External Reviewer, ACM Transactions on Software Engineering and Methodology (TOSEM)
External Reviewer, Springer Empirical Software Engineering (EMSE)

Mentoring

Tyler Stennett — Summer 2025 and 2026, Georgia Tech
Shuyang Liu — Summer 2025, UIUC
Myeongsoo Kim — Summer 2024, Georgia Tech · currently at Amazon Science
Ali Reza Ibrahimzada — Summer 2023 and 2024, UIUC

Selected News

Apr 2025 IBM Research Blog: ASTER: Natural and multi-language unit test generation with LLMs
Sep 2024 IBM Research Blog: Simplify your Code LLM solutions using CodeLLM DevKit
Jun 2022 Joined IBM Research as a Research Staff Member.
Jun 2022 Defended Ph.D. dissertation on decomposing deep learning models into modules.
Aug 2021 Microsoft Research Blog: Safe program merges at scale
May 2021 Awarded Research Excellence Award by the Department of Computer Science, Iowa State University.
Nov 2020 ACM SIGSOFT Distinguished Paper Award at ESEC/FSE 2020 for "On Decomposing Deep Neural Networks into Modules."
May 2020 2nd Place at the ACM Student Research Competition, ICSE 2020.
May 2020 Joined Microsoft Research as a Research Intern.