2024

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• TRACED: Execution-aware Pre-training for Source Code.

      by Y. Ding, B. Steenhoek, K. Pei, G. Kaiser, W. Le, B. Ray.

      [ICSE]

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2023

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• CONCORD: Clone-aware Contrastive Learning for Source Code.

      by Y. Ding, S. Chakraborty, L. Buratti, S. Pujar, A. Morari, G. Kaiser, B. Ray.

      ISSTA

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• Towards Greener Yet Powerful Code Generation via Quantization: An Empirical Study.  by X. Wei, S. Gonugondla, S. Wang, W. Ahmad, B. Ray, H. Qian, X. Li, V. Kumar, Z. Wang, Y. Tian, Q. Sun, B. Athiwaratkun, M. Shang, M. K. Ramanathan, P. Bhatia, B. Xiang.

      ESEC/FSE

 

• IvySyn: Automated Vulnerability Discovery for Deep Learning

      by Frameworks. N. Christou, D. Jin, V. Atlidakis, B. Ray, V. P. Kemerlis.

      Usenix Security

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• Multi-lingual Evaluation of Code Generation Models. by B. Athiwaratkun, S. Gouda, Z. Wang, X. Li , Y. Tian, M. Tan, W. Ahmad, S. Wang, Q. Sun, M. Shang, S. Gonugondla, H. Ding, V. Kumar, N. Fulton, A. Farahani, S. Jain, R. Giaquinto, H. Qian, M. Ramanathan, R. Nallapati, B. Ray, P. Bhatia, S. Sengupta, D. Roth, B. Xiang.

      ICLR Spotlight.

 

• Guided Conditional Diffusion for Controllable Traffic Simulation.

      by Z. Zhong, D. Rempe, D. Xu, Y. Chen, S. Veer, T. Che, B. Ray, M. Pavone. 

      ICRA

 

• ReCode: Robustness Evaluation of Code Generation Models.

      by S. Wang, Z. Li, H. Qian, C. Yang, Z. Wang, M. Shang, V. Kumar, S. Tan, B. Ray, P. Bhatia, R. Nallapati, M. K. Ramanathan, D. Roth, B.          Xiang.

      ACL
 

•  ContraCLM: Contrastive Learning For Causal Language Model.

       by N. Jain, D. Zhang, W. U. Ahmad, Z. Wang, F. Nan, X. Li, M. Tan, R. Nallapati, B. Ray, P. Bhatia, X. Ma, B. Xiang.

       ACL

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2022

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• NeuDep: Neural Binary Memory Dependence Analysis

       by Kexin Pei, Dongdong She, Michael Wang, Scott Geng, Zhou Xuan, Yaniv David, Junfeng Yang, Suman Jana, Baishakhi Ray

       FSE

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• NatGen: Generative pre-training by “Naturalizing” source code

       by Saikat Chakraborty, Toufique Ahmed, Yangruibo Ding, Premkumar Devanbu, Baishakhi Ray

       FSE

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• Detecting multi-sensor fusion errors in advanced driver-assistance systems

       by Ziyuan Zhong, Zhisheng Hu, Shengjian Guo, Xinyang Zhang, Zhenyu Zhong, Baishakhi Ray

       ISSTA

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• CARGO: AI-Guided Dependency Analysis for Migrating Monolithic Applications to Microservices Architecture

       by Vikram Nitin, Shubhi Asthana, Baishakhi Ray, Rahul Krishna

       ACM SIGSOFT Distinguished Paper Award.

       ASE

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• Neural network guided evolutionary fuzzing for finding traffic violations of autonomous vehicles

       by Ziyuan Zhong, Gail Kaiser, Baishakhi Ray

       TSE

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• Towards Learning (Dis)-Similarity of Source Code from Program Contrasts

       by Yangruibo Ding, Luca Buratti, Saurabh Pujar, Alessandro Morari, Baishakhi Ray, Saikat Chakraborty

       ACL

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• Unicorn: Reasoning about Configurable System Performance through the lens of Causality 

       by Shahriar Iqbal, Rahul Krishna, M.A. Javidian, Baishakhi Ray, Pooyan Jamshidi​

       EuroSys

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• VELVET: a noVel Ensemble Learning approach to automatically locate VulnErable sTatements.       

       by Yangruibo Ding, Sahil Suneja, Yunhui Zheng, Jim Laredo, Alessandro Morari, Gail Kaiser, Baishakhi Ray 

       SANER [slide] [code]

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• Predictive Synthesis of API-Centric Code.       

       by Daye Nam, Baishakhi Ray, Seohyun Kim, Xianshan Qu, Satish Chandra 

       MAPL 

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2021​

• On Multi-Modal Learning of Editing Source Code.                                                                                                                                by Saikat Chakraborty, Baishakhi Ray. ASE [slide] [code]

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• StateFormer: Fine-Grained Type Recovery from Binaries using Generative State Modeling.                                                               by Kexin Pei, Jonas Guan, Matthew Broughton, Zhongtian Chen, Songchen Yao, David Williams-King, Vikas Ummadisetty, Junfeng Yang, Baishakhi Ray, Suman Jana. FSE.  [code]​

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• Deep Learning-based Vulnerability Detection: Are we there yet?                                                                                                     by Saikat Chakraborty, Rahul Krishna, Yangruibo Ding, Baishakhi Ray. TSE.  [code]

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• Unified Pre-training for Program Understanding and Generation.                                                                                                    by Wasi Uddin Ahmad, Saikat Chakraborty, Baishakhi Ray, Kai-Wei Chang. NAACL-HLT 20221.  [code]

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• Retrieval Augmented Code Generation and Summarization.                                                                                                             by M. Rizwan Parvez, Wasi Ahmad, Saikat Chakraborty, Baishakhi Ray, & Kai-Wei Chang (2021).                                        EMNLP-findings. [code]

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• Understanding Local Robustness of Deep Neural Networks under Natural Variations.                                                                      by Ziyuan Zhong, Yuchi Tian, Baishakhi Ray. FASE 2021

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• DIRECT: A transformer-based Model for Decompiled Identifier Renaming.                                                                                       by Vikram Nitin, Anthony Saieva, Baishakhi Ray, Gail Kaiser. NLP4Prog 2021.                                                                     

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• PMFuzz: Test Case Generation for Persistent Memory Programs.                                                                                                        by Sihang Liu, Suyash Mahar, Baishakhi Ray, Samira Khan. ASPLOS 2021 

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2020

• Testing DNN Image Classifiers for Confusion & Bias Errors. 
  by Yuchi Tian, Ziyuan Zhong, Vicente Ordonez, Gail Kaiser, Baishakhi Ray. ICSE 2020.  [code, presentation]

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• MTFuzz: Fuzzing with a Multi-Task Neural Network. 

      by Dongdong She, Rahul Krishna, Lu Yan, Suman Jana, Baishakhi Ray. FSE 2020​.

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• Patching as Translation: the Data and the Metaphor. 

      by Yangruibo Ding, Baishakhi Ray, Premkumar Devanbu, Vincent J. Hellendoorn. ASE 2020.​

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• Multitask Learning Strengthens Adversarial Robustness. 

      by Chengzhi Mao, Amogh Gupta, Vikram Nitin, Baishakhi Ray, Shuran Song, Junfeng Yang, Carl Vondrick​

      ECCV 2020. 

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• Codit: Code Editing with Tree-Based Neural Models.

      by Saikat Chakraborty, Yangruibo Ding, Miltiadis Allamanis, Baishakhi Ray​

      TSE, ICSE'21 journal first. 

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• ConEx: Efficient Exploration of Big-Data System Configurations for Better Performance. 

      by Rahul Krishna, Chong Tang, Kevin Sullivan, Baishakhi Ray.​

      TSE, ICSE'21 journal first. 

 

• A Transformer-based Approach for Source Code Summarization. short paper. 

      by Wasi Uddin Ahmad, Saikat Chakraborty, Baishakhi Ray, Kai-Wei Chang. ACL 2020.​

      

• Neutaint: Efficient Dynamic Taint Analysis with Neural Networks.
  by Dongdong She, Yizheng Chen, Abhishek Shah, Baishakhi Ray, Suman Jana. S&P (Oakland) 2020

 

• An Empirical Study on the Use and Misuse of Java 8 Streams.
  by Raffi Khatchadourian, Yiming Tang, Mehdi Bagherzadeh, and Baishakhi Ray. FASE 2020.   Best Paper Award​

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2019

• Metric Learning for Adversarial Robustness, 10+8 pages, acceptance rate: 21.17%.
  by Chengzhi Mao, Ziyuan Zhong, Junfeng Yang, Carl Vondrick, Baishakhi Ray. NeurIPS 2019.  

 

• NEUZZ: Efficient Fuzzing with Neural Program Smoothing,13 pages, acceptance rate ~ 12%.
  by Dongdong She, Kexin Pei, Dave Epstein, Junfeng Yang, Baishakhi Ray, and Suman Jana. S&P (Oakland) 2019   

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• Toward Optimal Selection of Information Retrieval Models for Software Engineering Tasks.
  by Md Masudur Rahman, Saikat Chakraborty, Gail Kaiser, and Baishakhi Ray.  SCAM 2019

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2018

• DeepTest: Automated Testing of Deep-Neural-Network-driven Autonomous Cars, 10 pages, acceptance rate 20.9%.
  by Yuchi Tian, Kexin Pei, Suman Jana, Baishakhi Ray. ICSE 2018   Code

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• Building Language Models for Text with Named Entities, 10 pages, acceptance rate 24%.
  by Md Rizwan Parvez, Saikat Chakraborty, Baishakhi Ray, Kai-Wei Chang. ACL 2018  Code

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• Replay without Recording of Production Bugs for Service-Oriented Applications, 10 pages, acceptance rate 19.9%.
  by Nipun Arora, Jonathan Bell, Franjo Ivancic, Gail Kaiser, Baishakhi Ray. ASE 2018

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• Evaluating How Developers Use General-Purpose Web-Search for Code Retrieval, 10 pages, acceptance rate: 33%.
  by Md Masudur Rahman, Jed Barson, Sydney Paul, Joshua Kayani, Federico Andrés Lois, Sebastián Fernandez Quezada, Christopher Parnin, Kathryn T. Stolee, and Baishakhi Ray. MSR 2018

   

• Obfuscation Resilient Search through Executable Classification, Fang-Hsiang Su, Jonathan Bell, Gail Kaiser, and Baishakhi Ray, 10 pages. In Second ACM SIGPLAN Workshop on Machine Learning and Programming Languages. MAPL'18.

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2017

• Automatically Diagnosing and Repairing Error Handling Bugs in C, 10 pages, acceptance rate: 24.4%.
  by Yuchi Tian, Baishakhi Ray. FSE 2017 

      ACM SIGSOFT Distinguished Paper Award.
      Code

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• GitcProc: A Tool for Processing and Classifying GitHub Commits, 4 pages. by C. Casalnuovo, Y. Suchak, Baishakhi Ray, C. Rubio-Gonzalez.  ISSTA’17 Tool-demo. Code
   

• Some From Here, Some From There: Cross-Project Code Reuse in GitHub, 10 pages, acceptance rate: 27%..
  M. Gharehyazie, Baishakhi Ray, V. Filkov. MSR’17

      ACM SIGSOFT Distinguished Paper Award.
 

• A Large Scale Study of Programming Languages and Code Quality in Github.
  by B. Ray, D. Posnett, P. T. Devanbu, V. Filkov. CACM Research Highlights.

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2016

• APEx: Automated Inference of Error Specifications for C APIs, 10 pages, acceptance rate: 19.1%
  by Yuan Jochen Kang, Baishakhi Ray, Suman Jana.
  ASE 2016   Code

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• Automatically Detecting Error Handling Bugs using Error Specifications, 18 pages, acceptance rate: 15.5%
  by Suman Jana, Yuan Jochen Kang, Samuel Roth, Baishakhi Ray.
  USENIX Security 2016   Code

 

• On the “Naturalness” of Buggy Code, 12 pages, acceptance rate: 19%
  by Baishakhi Ray, Vincent Hellendoorn, Saheel Godhane, Zhaopeng Tu, Alberto Bacchelli, Premkumar Devanbu.
  ICSE 2016   Data   Slides   

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2015

• Assert Use in GitHub Projects, 11 pages, acceptance rate: 18.5%
  by Casey Casalnuovo, Prem Devanbu, Abilio Oliveira, Vladimir Filkov, Baishakhi Ray.
  ICSE 2015  
  A revised version of the paper is available here.

 

• The Uniqueness of Changes: Characteristics and Applications, 11 pages, acceptance rate: 30%
  by Baishakhi Ray, Meiyappan Nagappan, Christian Bird, Nachiappan Nagappan, Thomas Zimmermann.
  MSR 2015

 

• Gender and Tenure Diversity in GitHub Teams, 10 pages, acceptance rate: 20%.
  by Bogdan Vasilescu, Daryl Posnett, Baishakhi Ray, Mark van den Brand, Alexander Serebrenik, Premkumar Devanbu, Vladimir Filkov.  CHI 201

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2014

• A Large Scale Study of Programming Languages and Code Quality in Github, 10 pages, acceptance rate: 20%
  by Baishakhi Ray, Daryl Posnett, Vladimir Filkov, Premkumar T. Devanbu.  FSE 2014]

      Slides     
      Media Coverage: SlashDot, The Register, Reddit, InfoWorld, Hacker News

 

• Using Frankencerts for Automated Adversarial Testing of Certificate Validation in SSL/TLS Implementations   S&P 2014 Best Practical Paper Award, 16 pages, acceptance rate: 13%
  by Chad Brubaker, Suman Jana, Baishakhi Ray, Sarfraz Khurshid, Vitaly Shmatikov. S&P (Oakland) 2014

       Code   Slides     

       Media Coverage: Reddit, Golem, Heise

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2013

• Detecting and Characterizing Semantic Inconsistencies in Ported Code.   Nominated for distinguished paper award, Invited for journal special issue, 10 pages, acceptance rate: 23%
  by Baishakhi Ray, Miryung Kim, Suzette Person, Neha Rungta. ASE 2013   

      Slides   

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• An Empirical Study of API Stability and Adoption in the Android Ecosystem . 10 pages, acceptance rate: 22%
  by Tyler McDonnell, Baishakhi Ray, Miryung Kim. ICSM 2013

      Slides   

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2012

• A Case Study of Cross-System Porting in Forked Software Projects. 11 pages, acceptance rate: 17%
  by Baishakhi Ray, Miryung Kim. FSE 2012

      Slides   

 

• Repertoire: A Cross-System Porting Analysis Tool for Forked Software Projects . 4 pages
  by Baishakhi Ray, Christopher Wiley, Miryung Kim.  FSE 2012: Tool Demo

      Slides   

 

• An Empirical Study of Supplementary Bug Fixes. 10 pages, acceptance rate: 28%
  by Jihun Park, Miryung Kim, Baishakhi Ray, Doo-Hwan Bae. MSR 2012

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2011

• PTask: Operating System Abstractions To Manage GPUs as Compute Devices. 16 pages, acceptance rate: 17%
  by C. J. Rossbach, J. Currey, M. Silberstein, Baishakhi Ray, E. Witchel.  SOSP 2011   

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Older

• Touch Me Wear: Getting Physical with Social Networks, 6 pages
  by Aaron Beach, Baishakhi Ray, Leah Buechley
  Workshop on Sensor-based Models and Feedback Systems for Social Computing, associated with SocialCom 2009. DOI

 

• A Protocol for Building Secure and Reliable Covert Channel. 8 pages
  by Baishakhi Ray, Shivakant Mishra
  6th Annual Conference on Security and Privacy and Trust (PST 2008), Fredericton, NB, Canada. DOI

 

• WhozThat?: Evolving an Ecosystem for Context-Aware Mobile Social Networks. 6 pages
  by Aaron Beach, Mike Gartrell, Sirisha Akkala, Jack Elston, John Kelley, Keisuke Nishimoto, Baishakhi Ray, Sergei Razgulin, Karthik Sundaresan, Bonnie Surendar, Michael Terada, Richard Han
  IEEE Network Magazine Special Issue on Composable context-aware services, 2008. DOI

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Book Chapter

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• SecureWear: A Framework for Securing Mobile Social Networks .
  by Baishakhi Ray, Richard Han.
  In Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, Volume 85, Page 515-524

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