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2020 – today
- 2024
- [j14]Yangruibo Ding, Marcus J. Min, Gail E. Kaiser, Baishakhi Ray:
CYCLE: Learning to Self-Refine the Code Generation. Proc. ACM Program. Lang. 8(OOPSLA1): 392-418 (2024) - [j13]Gabriel Ryan, Siddhartha Jain, Mingyue Shang, Shiqi Wang, Xiaofei Ma, Murali Krishna Ramanathan, Baishakhi Ray:
Code-Aware Prompting: A Study of Coverage-Guided Test Generation in Regression Setting using LLM. Proc. ACM Softw. Eng. 1(FSE): 951-971 (2024) - [j12]Changshu Liu, Pelin Çetin, Yogesh Patodia, Baishakhi Ray, Saikat Chakraborty, Yangruibo Ding:
Automated Code Editing With Search-Generate-Modify. IEEE Trans. Software Eng. 50(7): 1675-1686 (2024) - [j11]Vikram Nitin, Anne Mulhern, Sanjay Arora, Baishakhi Ray:
Yuga: Automatically Detecting Lifetime Annotation Bugs in the Rust Language. IEEE Trans. Software Eng. 50(10): 2602-2613 (2024) - [c69]Marcus J. Min, Yangruibo Ding, Luca Buratti, Saurabh Pujar, Gail E. Kaiser, Suman Jana, Baishakhi Ray:
Beyond Accuracy: Evaluating Self-Consistency of Code Large Language Models with IdentityChain. ICLR 2024 - [c68]Yangruibo Ding, Benjamin Steenhoek, Kexin Pei, Gail E. Kaiser, Wei Le, Baishakhi Ray:
TRACED: Execution-aware Pre-training for Source Code. ICSE 2024: 36:1-36:12 - [c67]Md Mahbubur Rahman, Ira Ceka, Chengzhi Mao, Saikat Chakraborty, Baishakhi Ray, Wei Le:
Towards Causal Deep Learning for Vulnerability Detection. ICSE 2024: 153:1-153:11 - [c66]Changshu Liu, Pelin Çetin, Yogesh Patodia, Baishakhi Ray, Saikat Chakraborty, Yangruibo Ding:
Automated Code Editing with Search-Generate-Modify. ICSE Companion 2024: 398-399 - [e2]Vladimir Filkov, Baishakhi Ray, Minghui Zhou:
Proceedings of the 39th IEEE/ACM International Conference on Automated Software Engineering Workshops, ASEW 2024, Sacramento, CA, USA, 27 October 2024 - 1 November 2024. ACM 2024, ISBN 979-8-4007-1249-4 [contents] - [i75]Gabriel Ryan, Siddhartha Jain, Mingyue Shang, Shiqi Wang, Xiaofei Ma, Murali Krishna Ramanathan, Baishakhi Ray:
Code-Aware Prompting: A study of Coverage Guided Test Generation in Regression Setting using LLM. CoRR abs/2402.00097 (2024) - [i74]Jaywon Koo, Ziyan Yang, Paola Cascante-Bonilla, Baishakhi Ray, Vicente Ordonez:
PropTest: Automatic Property Testing for Improved Visual Programming. CoRR abs/2403.16921 (2024) - [i73]Yangruibo Ding, Yanjun Fu, Omniyyah Ibrahim, Chawin Sitawarin, Xinyun Chen, Basel Alomair, David A. Wagner, Baishakhi Ray, Yizheng Chen:
Vulnerability Detection with Code Language Models: How Far Are We? CoRR abs/2403.18624 (2024) - [i72]Yangruibo Ding, Marcus J. Min, Gail E. Kaiser, Baishakhi Ray:
CYCLE: Learning to Self-Refine the Code Generation. CoRR abs/2403.18746 (2024) - [i71]Yuhao Zhang, Shiqi Wang, Haifeng Qian, Zijian Wang, Mingyue Shang, Linbo Liu, Sanjay Krishna Gouda, Baishakhi Ray, Murali Krishna Ramanathan, Xiaofei Ma, Anoop Deoras:
CodeFort: Robust Training for Code Generation Models. CoRR abs/2405.01567 (2024) - [i70]Michael R. Lyu, Baishakhi Ray, Abhik Roychoudhury, Shin Hwei Tan, Patanamon Thongtanunam:
Automatic Programming: Large Language Models and Beyond. CoRR abs/2405.02213 (2024) - [i69]Vikram Nitin, Baishakhi Ray:
SpecTra: Enhancing the Code Translation Ability of Language Models by Generating Multi-Modal Specifications. CoRR abs/2405.18574 (2024) - [i68]Nan Jiang, Xiaopeng Li, Shiqi Wang, Qiang Zhou, Soneya Binta Hossain, Baishakhi Ray, Varun Kumar, Xiaofei Ma, Anoop Deoras:
Training LLMs to Better Self-Debug and Explain Code. CoRR abs/2405.18649 (2024) - [i67]Yangruibo Ding, Jinjun Peng, Marcus J. Min, Gail E. Kaiser, Junfeng Yang, Baishakhi Ray:
SemCoder: Training Code Language Models with Comprehensive Semantics. CoRR abs/2406.01006 (2024) - [i66]Junlin Wang, Siddhartha Jain, Dejiao Zhang, Baishakhi Ray, Varun Kumar, Ben Athiwaratkun:
Reasoning in Token Economies: Budget-Aware Evaluation of LLM Reasoning Strategies. CoRR abs/2406.06461 (2024) - [i65]Alex Mathai, Chenxi Huang, Petros Maniatis, Aleksandr Nogikh, Franjo Ivancic, Junfeng Yang, Baishakhi Ray:
KGym: A Platform and Dataset to Benchmark Large Language Models on Linux Kernel Crash Resolution. CoRR abs/2407.02680 (2024) - [i64]Shmuel Berman, Kathleen R. McKeown, Baishakhi Ray:
Solving Zebra Puzzles Using Constraint-Guided Multi-Agent Systems. CoRR abs/2407.03956 (2024) - [i63]Nihal Jain, Robert Kwiatkowski, Baishakhi Ray, Murali Krishna Ramanathan, Varun Kumar:
On Mitigating Code LLM Hallucinations with API Documentation. CoRR abs/2407.09726 (2024) - [i62]Dongdong She, Kexin Pei, Junfeng Yang, Baishakhi Ray, Suman Jana:
Comment on Revisiting Neural Program Smoothing for Fuzzing. CoRR abs/2409.04504 (2024) - 2023
- [j10]Ziyuan Zhong, Gail E. Kaiser, Baishakhi Ray:
Neural Network Guided Evolutionary Fuzzing for Finding Traffic Violations of Autonomous Vehicles. IEEE Trans. Software Eng. 49(4): 1860-1875 (2023) - [j9]Kexin Pei, Zhou Xuan, Junfeng Yang, Suman Jana, Baishakhi Ray:
Learning Approximate Execution Semantics From Traces for Binary Function Similarity. IEEE Trans. Software Eng. 49(4): 2776-2790 (2023) - [c65]Hantian Ding, Varun Kumar, Yuchen Tian, Zijian Wang, Rob Kwiatkowski, Xiaopeng Li, Murali Krishna Ramanathan, Baishakhi Ray, Parminder Bhatia, Sudipta Sengupta:
A Static Evaluation of Code Completion by Large Language Models. ACL (industry) 2023: 347-360 - [c64]Nihal Jain, Dejiao Zhang, Wasi Uddin Ahmad, Zijian Wang, Feng Nan, Xiaopeng Li, Ming Tan, Ramesh Nallapati, Baishakhi Ray, Parminder Bhatia, Xiaofei Ma, Bing Xiang:
ContraCLM: Contrastive Learning For Causal Language Model. ACL (1) 2023: 6436-6459 - [c63]Shiqi Wang, Zheng Li, Haifeng Qian, Chenghao Yang, Zijian Wang, Mingyue Shang, Varun Kumar, Samson Tan, Baishakhi Ray, Parminder Bhatia, Ramesh Nallapati, Murali Krishna Ramanathan, Dan Roth, Bing Xiang:
ReCode: Robustness Evaluation of Code Generation Models. ACL (1) 2023: 13818-13843 - [c62]Md Shahriar Iqbal, Ziyuan Zhong, Iftakhar Ahmad, Baishakhi Ray, Pooyan Jamshidi:
CAMEO: A Causal Transfer Learning Approach for Performance Optimization of Configurable Computer Systems. SoCC 2023: 555-571 - [c61]Ziyuan Zhong, Davis Rempe, Yuxiao Chen, Boris Ivanovic, Yulong Cao, Danfei Xu, Marco Pavone, Baishakhi Ray:
Language-Guided Traffic Simulation via Scene-Level Diffusion. CoRL 2023: 144-177 - [c60]Wasi Uddin Ahmad, Saikat Chakraborty, Baishakhi Ray, Kai-Wei Chang:
Summarize and Generate to Back-translate: Unsupervised Translation of Programming Languages. EACL 2023: 1520-1534 - [c59]Ziyuan Zhong, Davis Rempe, Danfei Xu, Yuxiao Chen, Sushant Veer, Tong Che, Baishakhi Ray, Marco Pavone:
Guided Conditional Diffusion for Controllable Traffic Simulation. ICRA 2023: 3560-3566 - [c58]Aniketh Malyala, Katelyn Zhou, Baishakhi Ray, Saikat Chakraborty:
On ML-Based Program Translation: Perils and Promises. ICSE (NIER) 2023: 60-65 - [c57]Baishakhi Ray:
Programming Language Processing : How AI can Revolutionize Software Development? ISEC 2023: 1:1 - [c56]Yangruibo Ding, Saikat Chakraborty, Luca Buratti, Saurabh Pujar, Alessandro Morari, Gail E. Kaiser, Baishakhi Ray:
CONCORD: Clone-Aware Contrastive Learning for Source Code. ISSTA 2023: 26-38 - [c55]Xiaokai Wei, Sujan Kumar Gonugondla, Shiqi Wang, Wasi Uddin Ahmad, Baishakhi Ray, Haifeng Qian, Xiaopeng Li, Varun Kumar, Zijian Wang, Yuchen Tian, Qing Sun, Ben Athiwaratkun, Mingyue Shang, Murali Krishna Ramanathan, Parminder Bhatia, Bing Xiang:
Towards Greener Yet Powerful Code Generation via Quantization: An Empirical Study. ESEC/SIGSOFT FSE 2023: 224-236 - [c54]Neophytos Christou, Di Jin, Vaggelis Atlidakis, Baishakhi Ray, Vasileios P. Kemerlis:
IvySyn: Automated Vulnerability Discovery in Deep Learning Frameworks. USENIX Security Symposium 2023: 2383-2400 - [e1]Marcel Böhme, Yannic Noller, Baishakhi Ray, László Szekeres:
Proceedings of the 2nd International Fuzzing Workshop, FUZZING 2023, Seattle, WA, USA, 17 July 2023. ACM 2023 [contents] - [i61]Aniketh Malyala, Katelyn Zhou, Baishakhi Ray, Saikat Chakraborty:
On ML-Based Program Translation: Perils and Promises. CoRR abs/2302.10812 (2023) - [i60]Xiaokai Wei, Sujan K. Gonugondla, Wasi Uddin Ahmad, Shiqi Wang, Baishakhi Ray, Haifeng Qian, Xiaopeng Li, Varun Kumar, Zijian Wang, Yuchen Tian, Qing Sun, Ben Athiwaratkun, Mingyue Shang, Murali Krishna Ramanathan, Parminder Bhatia, Bing Xiang:
Greener yet Powerful: Taming Large Code Generation Models with Quantization. CoRR abs/2303.05378 (2023) - [i59]Jaspreet Ranjit, Tianlu Wang, Baishakhi Ray, Vicente Ordonez:
Variation of Gender Biases in Visual Recognition Models Before and After Finetuning. CoRR abs/2303.07615 (2023) - [i58]Islem Bouzenia, Yangruibo Ding, Kexin Pei, Baishakhi Ray, Michael Pradel:
TraceFixer: Execution Trace-Driven Program Repair. CoRR abs/2304.12743 (2023) - [i57]Hantian Ding, Varun Kumar, Yuchen Tian, Zijian Wang, Rob Kwiatkowski, Xiaopeng Li, Murali Krishna Ramanathan, Baishakhi Ray, Parminder Bhatia, Sudipta Sengupta, Dan Roth, Bing Xiang:
A Static Evaluation of Code Completion by Large Language Models. CoRR abs/2306.03203 (2023) - [i56]Yangruibo Ding, Saikat Chakraborty, Luca Buratti, Saurabh Pujar, Alessandro Morari, Gail E. Kaiser, Baishakhi Ray:
CONCORD: Clone-aware Contrastive Learning for Source Code. CoRR abs/2306.03234 (2023) - [i55]Ziyuan Zhong, Davis Rempe, Yuxiao Chen, Boris Ivanovic, Yulong Cao, Danfei Xu, Marco Pavone, Baishakhi Ray:
Language-Guided Traffic Simulation via Scene-Level Diffusion. CoRR abs/2306.06344 (2023) - [i54]Changshu Liu, Pelin Çetin, Yogesh Patodia, Saikat Chakraborty, Yangruibo Ding, Baishakhi Ray:
Automated Code Editing with Search-Generate-Modify. CoRR abs/2306.06490 (2023) - [i53]Yangruibo Ding, Benjamin Steenhoek, Kexin Pei, Gail E. Kaiser, Wei Le, Baishakhi Ray:
TRACED: Execution-aware Pre-training for Source Code. CoRR abs/2306.07487 (2023) - [i52]Md Shahriar Iqbal, Ziyuan Zhong, Iftakhar Ahmad, Baishakhi Ray, Pooyan Jamshidi:
CAMEO: A Causal Transfer Learning Approach for Performance Optimization of Configurable Computer Systems. CoRR abs/2306.07888 (2023) - [i51]Md Mahbubur Rahman, Ira Ceka, Chengzhi Mao, Saikat Chakraborty, Baishakhi Ray, Wei Le:
Towards Causal Deep Learning for Vulnerability Detection. CoRR abs/2310.07958 (2023) - [i50]Vikram Nitin, Anne Mulhern, Sanjay Arora, Baishakhi Ray:
Yuga: Automatically Detecting Lifetime Annotation Bugs in the Rust Language. CoRR abs/2310.08507 (2023) - [i49]Marcus J. Min, Yangruibo Ding, Luca Buratti, Saurabh Pujar, Gail E. Kaiser, Suman Jana, Baishakhi Ray:
Beyond Accuracy: Evaluating Self-Consistency of Code Large Language Models with IdentityChain. CoRR abs/2310.14053 (2023) - [i48]Michael Pradel, Baishakhi Ray, Charles Sutton, Eran Yahav:
Programming Language Processing (Dagstuhl Seminar 23062). Dagstuhl Reports 13(2): 20-32 (2023) - 2022
- [j8]Rahul Krishna, Chong Tang, Kevin J. Sullivan, Baishakhi Ray:
ConEx: Efficient Exploration of Big-Data System Configurations for Better Performance. IEEE Trans. Software Eng. 48(3): 893-909 (2022) - [j7]Saikat Chakraborty, Yangruibo Ding, Miltiadis Allamanis, Baishakhi Ray:
CODIT: Code Editing With Tree-Based Neural Models. IEEE Trans. Software Eng. 48(4): 1385-1399 (2022) - [j6]Saikat Chakraborty, Rahul Krishna, Yangruibo Ding, Baishakhi Ray:
Deep Learning Based Vulnerability Detection: Are We There Yet? IEEE Trans. Software Eng. 48(9): 3280-3296 (2022) - [c53]Yangruibo Ding, Luca Buratti, Saurabh Pujar, Alessandro Morari, Baishakhi Ray, Saikat Chakraborty:
Towards Learning (Dis)-Similarity of Source Code from Program Contrasts. ACL (1) 2022: 6300-6312 - [c52]Md Shahriar Iqbal, Rahul Krishna, Mohammad Ali Javidian, Baishakhi Ray, Pooyan Jamshidi:
Unicorn: reasoning about configurable system performance through the lens of causality. EuroSys 2022: 199-217 - [c51]Ziyuan Zhong, Zhisheng Hu, Shengjian Guo, Xinyang Zhang, Zhenyu Zhong, Baishakhi Ray:
Detecting multi-sensor fusion errors in advanced driver-assistance systems. ISSTA 2022: 493-505 - [c50]Vikram Nitin, Shubhi Asthana, Baishakhi Ray, Rahul Krishna:
CARGO: AI-Guided Dependency Analysis for Migrating Monolithic Applications to Microservices Architecture. ASE 2022: 20:1-20:12 - [c49]Daye Nam, Baishakhi Ray, Seohyun Kim, Xianshan Qu, Satish Chandra:
Predictive synthesis of API-centric code. MAPS@PLDI 2022: 40-49 - [c48]Saikat Chakraborty, Toufique Ahmed, Yangruibo Ding, Premkumar T. Devanbu, Baishakhi Ray:
NatGen: generative pre-training by "naturalizing" source code. ESEC/SIGSOFT FSE 2022: 18-30 - [c47]Kexin Pei, Dongdong She, Michael Wang, Scott Geng, Zhou Xuan, Yaniv David, Junfeng Yang, Suman Jana, Baishakhi Ray:
NeuDep: neural binary memory dependence analysis. ESEC/SIGSOFT FSE 2022: 747-759 - [c46]Yangruibo Ding, Sahil Suneja, Yunhui Zheng, Jim Laredo, Alessandro Morari, Gail E. Kaiser, Baishakhi Ray:
VELVET: a noVel Ensemble Learning approach to automatically locate VulnErable sTatements. SANER 2022: 959-970 - [i47]Daye Nam, Baishakhi Ray, Seohyun Kim, Xianshan Qu, Satish Chandra:
Predictive Synthesis of API-Centric Code. CoRR abs/2201.03758 (2022) - [i46]Md Shahriar Iqbal, Rahul Krishna, Mohammad Ali Javidian, Baishakhi Ray, Pooyan Jamshidi:
Unicorn: Reasoning about Configurable System Performance through the lens of Causality. CoRR abs/2201.08413 (2022) - [i45]Ziyuan Zhong, Yuchi Tian, Conor J. Sweeney, Vicente Ordóñez Román, Baishakhi Ray:
Repairing Group-Level Errors for DNNs Using Weighted Regularization. CoRR abs/2203.13612 (2022) - [i44]Wasi Uddin Ahmad, Saikat Chakraborty, Baishakhi Ray, Kai-Wei Chang:
Summarize and Generate to Back-translate: Unsupervised Translation of Programming Languages. CoRR abs/2205.11116 (2022) - [i43]Saikat Chakraborty, Toufique Ahmed, Yangruibo Ding, Premkumar T. Devanbu, Baishakhi Ray:
NatGen: Generative pre-training by "Naturalizing" source code. CoRR abs/2206.07585 (2022) - [i42]Yun Tang, Yuan Zhou, Kairui Yang, Ziyuan Zhong, Baishakhi Ray, Yang Liu, Ping Zhang, Junbo Chen:
Automatic Map Generation for Autonomous Driving System Testing. CoRR abs/2206.09357 (2022) - [i41]Vikram Nitin, Shubhi Asthana, Baishakhi Ray, Rahul Krishna:
CARGO: AI-Guided Dependency Analysis for Migrating Monolithic Applications to Microservices Architecture. CoRR abs/2207.11784 (2022) - [i40]Neophytos Christou, Di Jin, Vaggelis Atlidakis, Baishakhi Ray, Vasileios P. Kemerlis:
IvySyn: Automated Vulnerability Discovery for Deep Learning Frameworks. CoRR abs/2209.14921 (2022) - [i39]Nihal Jain, Dejiao Zhang, Wasi Uddin Ahmad, Zijian Wang, Feng Nan, Xiaopeng Li, Ming Tan, Ramesh Nallapati, Baishakhi Ray, Parminder Bhatia, Xiaofei Ma, Bing Xiang:
ContraGen: Effective Contrastive Learning For Causal Language Model. CoRR abs/2210.01185 (2022) - [i38]Kexin Pei, Dongdong She, Michael Wang, Scott Geng, Zhou Xuan, Yaniv David, Junfeng Yang, Suman Jana, Baishakhi Ray:
NeuDep: Neural Binary Memory Dependence Analysis. CoRR abs/2210.02853 (2022) - [i37]Ben Athiwaratkun, Sanjay Krishna Gouda, Zijian Wang, Xiaopeng Li, Yuchen Tian, Ming Tan, Wasi Uddin Ahmad, Shiqi Wang, Qing Sun, Mingyue Shang, Sujan Kumar Gonugondla, Hantian Ding, Varun Kumar, Nathan Fulton, Arash Farahani, Siddhartha Jain, Robert Giaquinto, Haifeng Qian, Murali Krishna Ramanathan, Ramesh Nallapati, Baishakhi Ray, Parminder Bhatia, Sudipta Sengupta, Dan Roth, Bing Xiang:
Multi-lingual Evaluation of Code Generation Models. CoRR abs/2210.14868 (2022) - [i36]Ziyuan Zhong, Davis Rempe, Danfei Xu, Yuxiao Chen, Sushant Veer, Tong Che, Baishakhi Ray, Marco Pavone:
Guided Conditional Diffusion for Controllable Traffic Simulation. CoRR abs/2210.17366 (2022) - [i35]Shiqi Wang, Zheng Li, Haifeng Qian, Chenghao Yang, Zijian Wang, Mingyue Shang, Varun Kumar, Samson Tan, Baishakhi Ray, Parminder Bhatia, Ramesh Nallapati, Murali Krishna Ramanathan, Dan Roth, Bing Xiang:
ReCode: Robustness Evaluation of Code Generation Models. CoRR abs/2212.10264 (2022) - 2021
- [c45]Sihang Liu, Suyash Mahar, Baishakhi Ray, Samira Manabi Khan:
PMFuzz: test case generation for persistent memory programs. ASPLOS 2021: 487-502 - [c44]Md. Rizwan Parvez, Wasi Uddin Ahmad, Saikat Chakraborty, Baishakhi Ray, Kai-Wei Chang:
Retrieval Augmented Code Generation and Summarization. EMNLP (Findings) 2021: 2719-2734 - [c43]Ziyuan Zhong, Yuchi Tian, Baishakhi Ray:
Understanding Local Robustness of Deep Neural Networks under Natural Variations. FASE 2021: 313-337 - [c42]Saikat Chakraborty, Baishakhi Ray:
On Multi-Modal Learning of Editing Source Code. ASE 2021: 443-455 - [c41]Wasi Uddin Ahmad, Saikat Chakraborty, Baishakhi Ray, Kai-Wei Chang:
Unified Pre-training for Program Understanding and Generation. NAACL-HLT 2021: 2655-2668 - [c40]Kexin Pei, Jonas Guan, Matthew Broughton, Zhongtian Chen, Songchen Yao, David Williams-King, Vikas Ummadisetty, Junfeng Yang, Baishakhi Ray, Suman Jana:
StateFormer: fine-grained type recovery from binaries using generative state modeling. ESEC/SIGSOFT FSE 2021: 690-702 - [i34]Wasi Uddin Ahmad, Saikat Chakraborty, Baishakhi Ray, Kai-Wei Chang:
Unified Pre-training for Program Understanding and Generation. CoRR abs/2103.06333 (2021) - [i33]Saikat Chakraborty, Baishakhi Ray:
On Multi-Modal Learning of Editing Source Code. CoRR abs/2108.06645 (2021) - [i32]Md. Rizwan Parvez, Wasi Uddin Ahmad, Saikat Chakraborty, Baishakhi Ray, Kai-Wei Chang:
Retrieval Augmented Code Generation and Summarization. CoRR abs/2108.11601 (2021) - [i31]Ziyuan Zhong, Gail E. Kaiser, Baishakhi Ray:
Neural Network Guided Evolutionary Fuzzing for Finding Traffic Violations of Autonomous Vehicles. CoRR abs/2109.06126 (2021) - [i30]Ziyuan Zhong, Zhisheng Hu, Shengjian Guo, Xinyang Zhang, Zhenyu Zhong, Baishakhi Ray:
Detecting Safety Problems of Multi-Sensor Fusion in Autonomous Driving. CoRR abs/2109.06404 (2021) - [i29]Yangruibo Ding, Luca Buratti, Saurabh Pujar, Alessandro Morari, Baishakhi Ray, Saikat Chakraborty:
Contrastive Learning for Source Code with Structural and Functional Properties. CoRR abs/2110.03868 (2021) - [i28]Ziyuan Zhong, Yun Tang, Yuan Zhou, Vânia de Oliveira Neves, Yang Liu, Baishakhi Ray:
A Survey on Scenario-Based Testing for Automated Driving Systems in High-Fidelity Simulation. CoRR abs/2112.00964 (2021) - [i27]Yangruibo Ding, Sahil Suneja, Yunhui Zheng, Jim Laredo, Alessandro Morari, Gail E. Kaiser, Baishakhi Ray:
VELVET: a noVel Ensemble Learning approach to automatically locate VulnErable sTatements. CoRR abs/2112.10893 (2021) - 2020
- [c39]Wasi Uddin Ahmad, Saikat Chakraborty, Baishakhi Ray, Kai-Wei Chang:
A Transformer-based Approach for Source Code Summarization. ACL 2020: 4998-5007 - [c38]Chengzhi Mao, Amogh Gupta, Vikram Nitin, Baishakhi Ray, Shuran Song, Junfeng Yang, Carl Vondrick:
Multitask Learning Strengthens Adversarial Robustness. ECCV (2) 2020: 158-174 - [c37]Raffi Khatchadourian, Yiming Tang, Mehdi Bagherzadeh, Baishakhi Ray:
An Empirical Study on the Use and Misuse of Java 8 Streams. FASE 2020: 97-118 - [c36]Yuchi Tian, Ziyuan Zhong, Vicente Ordonez, Gail E. Kaiser, Baishakhi Ray:
Testing DNN image classifiers for confusion & bias errors. ICSE (Companion Volume) 2020: 304-305 - [c35]Yuchi Tian, Ziyuan Zhong, Vicente Ordonez, Gail E. Kaiser, Baishakhi Ray:
Testing DNN image classifiers for confusion & bias errors. ICSE 2020: 1122-1134 - [c34]Yangruibo Ding, Baishakhi Ray, Premkumar T. Devanbu, Vincent J. Hellendoorn:
Patching as Translation: the Data and the Metaphor. ASE 2020: 275-286 - [c33]Dongdong She, Rahul Krishna, Lu Yan, Suman Jana, Baishakhi Ray:
MTFuzz: fuzzing with a multi-task neural network. ESEC/SIGSOFT FSE 2020: 737-749 - [c32]Dongdong She, Yizheng Chen, Abhishek Shah, Baishakhi Ray, Suman Jana:
Neutaint: Efficient Dynamic Taint Analysis with Neural Networks. SP 2020: 1527-1543 - [i26]Wasi Uddin Ahmad, Saikat Chakraborty, Baishakhi Ray, Kai-Wei Chang:
A Transformer-based Approach for Source Code Summarization. CoRR abs/2005.00653 (2020) - [i25]Vaggelis Atlidakis, Roxana Geambasu, Patrice Godefroid, Marina Polishchuk, Baishakhi Ray:
Pythia: Grammar-Based Fuzzing of REST APIs with Coverage-guided Feedback and Learning-based Mutations. CoRR abs/2005.11498 (2020) - [i24]Dongdong She, Rahul Krishna, Lu Yan, Suman Jana, Baishakhi Ray:
MTFuzz: Fuzzing with a Multi-Task Neural Network. CoRR abs/2005.12392 (2020) - [i23]Chengzhi Mao, Amogh Gupta, Vikram Nitin, Baishakhi Ray, Shuran Song, Junfeng Yang, Carl Vondrick:
Multitask Learning Strengthens Adversarial Robustness. CoRR abs/2007.07236 (2020) - [i22]Yangruibo Ding, Baishakhi Ray, Premkumar T. Devanbu, Vincent J. Hellendoorn:
Patching as Translation: the Data and the Metaphor. CoRR abs/2008.10707 (2020) - [i21]Saikat Chakraborty, Rahul Krishna, Yangruibo Ding, Baishakhi Ray:
Deep Learning based Vulnerability Detection: Are We There Yet? CoRR abs/2009.07235 (2020) - [i20]Prem Devanbu, Matthew B. Dwyer, Sebastian G. Elbaum, Michael Lowry, Kevin Moran, Denys Poshyvanyk, Baishakhi Ray, Rishabh Singh, Xiangyu Zhang:
Deep Learning & Software Engineering: State of Research and Future Directions. CoRR abs/2009.08525 (2020) - [i19]Ziyuan Zhong, Yuchi Tian, Baishakhi Ray:
Understanding Spatial Robustness of Deep Neural Networks. CoRR abs/2010.04821 (2020) - [i18]Rahul Krishna, Md Shahriar Iqbal, Mohammad Ali Javidian, Baishakhi Ray, Pooyan Jamshidi:
CADET: A Systematic Method For Debugging Misconfigurations using Counterfactual Reasoning. CoRR abs/2010.06061 (2020) - [i17]Kexin Pei, Zhou Xuan, Junfeng Yang, Suman Jana, Baishakhi Ray:
Trex: Learning Execution Semantics from Micro-Traces for Binary Similarity. CoRR abs/2012.08680 (2020)
2010 – 2019
- 2019
- [j5]Mohammad Gharehyazie, Baishakhi Ray, Mehdi Keshani, Masoumeh Soleimani Zavosht, Abbas Heydarnoori, Vladimir Filkov:
Cross-project code clones in GitHub. Empir. Softw. Eng. 24(3): 1538-1573 (2019) - [j4]Kexin Pei, Shiqi Wang, Yuchi Tian, Justin Whitehouse, Carl Vondrick, Yinzhi Cao, Baishakhi Ray, Suman Jana, Junfeng Yang:
Bringing Engineering Rigor to Deep Learning. ACM SIGOPS Oper. Syst. Rev. 53(1): 59-67 (2019) - [c31]