A comprehensive study on deep learning bug characteristics. - Md Johirul Islam; Giang Nguyen; Rangeet Pan; Hridesh Rajan (ESEC/SIGSOFT FSE, 2019)

Static deep neural network analysis for robustness. - Rangeet Pan (ESEC/SIGSOFT FSE, 2019)

Identifying Classes Susceptible to Adversarial Attacks. - Rangeet Pan; Md Johirul Islam; Shibbir Ahmed; Hridesh Rajan (CoRR, 2019)

What Do Developers Ask About ML Libraries? A Large-scale Study Using Stack Overflow. - Md Johirul Islam; Hoan Anh Nguyen; Rangeet Pan; Hridesh Rajan (CoRR, 2019)

Repairing deep neural networks: fix patterns and challenges. - Md Johirul Islam; Rangeet Pan; Giang Nguyen; Hridesh Rajan (ICSE, 2020)

Does fixing bug increase robustness in deep learning? - Rangeet Pan (ICSE (Companion Volume), 2020)

On decomposing a deep neural network into modules. - Rangeet Pan; Hridesh Rajan (ESEC/SIGSOFT FSE, 2020)

Can Program Synthesis be Used to Learn Merge Conflict Resolutions? An Empirical Analysis. - Rangeet Pan; Vu Le 002; Nachiappan Nagappan; Sumit Gulwani; Shuvendu K. Lahiri; Mike Kaufman (ICSE, 2021)

Manas: Mining Software Repositories to Assist AutoML. - Giang Nguyen; Johir Islam; Rangeet Pan; Hridesh Rajan (CoRR, 2021)

Manas: Mining Software Repositories to Assist AutoML. - Giang Nguyen; Md Johirul Islam; Rangeet Pan; Hridesh Rajan (ICSE, 2022)

Decomposing Convolutional Neural Networks into Reusable and Replaceable Modules. - Rangeet Pan; Hridesh Rajan (ICSE, 2022)

An Empirical Study on the Bugs Found while Reusing Pre-trained Natural Language Processing Models. - Rangeet Pan; Sumon Biswas; Mohna Chakraborty; Breno Dantas Cruz; Hridesh Rajan (CoRR, 2022)

Decomposing a Recurrent Neural Network into Modules for Enabling Reusability and Replacement. - Sayem Mohammad Imtiaz; Fraol Batole; Astha Singh; Rangeet Pan; Breno Dantas Cruz; Hridesh Rajan (ICSE, 2023)

Understanding the Effectiveness of Large Language Models in Code Translation. - Rangeet Pan; Ali Reza Ibrahimzada; Rahul Krishna; Divya Sankar; Lambert Pouguem Wassi; Michele Merler; Boris Sobolev; Raju Pavuluri; Saurabh Sinha; Reyhaneh Jabbarvand (CoRR, 2023)

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; Reyhaneh Jabbarvand (ICSE, 2024)

Multi-language Unit Test Generation using LLMs. - Rangeet Pan; Myeongsoo Kim; Rahul Krishna; Raju Pavuluri; Saurabh Sinha (CoRR, 2024)

Repository-Level Compositional Code Translation and Validation. - Ali Reza Ibrahimzada; Kaiyao Ke; Mrigank Pawagi; Muhammad Salman Abid; Rangeet Pan; Saurabh Sinha; Reyhaneh Jabbarvand (CoRR, 2024)

TDD-Bench Verified: Can LLMs Generate Tests for Issues Before They Get Resolved? - Toufique Ahmed; Martin Hirzel; Rangeet Pan; Avraham Shinnar; Saurabh Sinha (CoRR, 2024)

Codellm-Devkit: A Framework for Contextualizing Code LLMs with Program Analysis Insights. - Rahul Krishna; Rangeet Pan; Saurabh Sinha; Srikanth Tamilselvam; Raju Pavuluri; Maja Vukovic (SIGSOFT FSE Companion, 2025)

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; Reyhaneh Jabbarvand (Proc. ACM Softw. Eng., 2025)

Otter: Generating Tests from Issues to Validate SWE Patches. - Toufique Ahmed; Jatin Ganhotra; Rangeet Pan; Avraham Shinnar; Saurabh Sinha; Martin Hirzel (CoRR, 2025)