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ORCIDAditya Kanade
This is just a disambiguation page, and is not intended to be the bibliography of an actual person. Any publication listed on this page has not been assigned to an actual author yet. If you know the true author of one of the publications listed below, you are welcome to contact us.
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2020 – today
- 2024
[j6]Ramakrishna Bairi
, Atharv Sonwane, Aditya Kanade, Vageesh D. C., Arun Iyer, Suresh Parthasarathy, Sriram K. Rajamani, Balasubramanyan Ashok, Shashank Shet:
CodePlan: Repository-Level Coding using LLMs and Planning. Proc. ACM Softw. Eng. 1(FSE): 675-698 (2024)- [j5]Nalin Wadhwa, Jui Pradhan, Atharv Sonwane, Surya Prakash Sahu, Nagarajan Natarajan, Aditya Kanade, Suresh Parthasarathy, Sriram K. Rajamani:
CORE: Resolving Code Quality Issues using LLMs. Proc. ACM Softw. Eng. 1(FSE): 789-811 (2024) - [c35]Harshit Joshi, Abishai Ebenezer, José Pablo Cambronero Sánchez, Sumit Gulwani, Aditya Kanade, Vu Le, Ivan Radicek, Gust Verbruggen:
FLAME: A Small Language Model for Spreadsheet Formulas. AAAI 2024: 12995-13003 - [c34]Surya Prakash Sahu, Madhurima Mandal, Shikhar Bharadwaj, Aditya Kanade, Petros Maniatis, Shirish K. Shevade:
CodeQueries: A Dataset of Semantic Queries over Code. ISEC 2024: 7:1-7:11 - [i26]Manav Singhal, Tushar Aggarwal, Abhijeet Awasthi, Nagarajan Natarajan, Aditya Kanade:
NoFunEval: Funny How Code LMs Falter on Requirements Beyond Functional Correctness. CoRR abs/2401.15963 (2024) - [i25]Ajinkya Pankaj Deshpande, Anmol Agarwal, Shashank Shet, Arun Iyer, Aditya Kanade, Ramakrishna Bairi, Suresh Parthasarathy:
Class-Level Code Generation from Natural Language Using Iterative, Tool-Enhanced Reasoning over Repository. CoRR abs/2405.01573 (2024) - [i24]Daman Arora, Atharv Sonwane, Nalin Wadhwa, Abhav Mehrotra, Saiteja Utpala, Ramakrishna Bairi, Aditya Kanade, Nagarajan Natarajan:
MASAI: Modular Architecture for Software-engineering AI Agents. CoRR abs/2406.11638 (2024) - [i23]Usneek Singh, José Cambronero, Sumit Gulwani, Aditya Kanade, Anirudh Khatry, Vu Le, Mukul Singh, Gust Verbruggen:
An Empirical Study of Validating Synthetic Data for Formula Generation. CoRR abs/2407.10657 (2024) - 2023
- [c33]Aditya Kanade, Mansi Sharma, Manivannan Muniyandi:
Attention-Guided Deep Learning Framework For Movement Quality Assessment. ICASSP 2023: 1-5 - [c32]Lakshya A. Agrawal, Aditya Kanade, Navin Goyal, Shuvendu K. Lahiri, Sriram K. Rajamani:
Monitor-Guided Decoding of Code LMs with Static Analysis of Repository Context. NeurIPS 2023 - [c31]Priyanshu Gupta, Avishree Khare, Yasharth Bajpai, Saikat Chakraborty, Sumit Gulwani, Aditya Kanade, Arjun Radhakrishna, Gustavo Soares, Ashish Tiwari:
Grace: Language Models Meet Code Edits. ESEC/SIGSOFT FSE 2023: 1483-1495 - [i22]Harshit Joshi, Abishai Ebenezer, José Cambronero, Sumit Gulwani, Aditya Kanade, Vu Le, Ivan Radicek, Gust Verbruggen:
FLAME: A small language model for spreadsheet formulas. CoRR abs/2301.13779 (2023) - [i21]Priyanshu Gupta, Avishree Khare, Yasharth Bajpai, Saikat Chakraborty, Sumit Gulwani, Aditya Kanade, Arjun Radhakrishna, Gustavo Soares, Ashish Tiwari:
GrACE: Generation using Associated Code Edits. CoRR abs/2305.14129 (2023) - [i20]Lakshya A. Agrawal, Aditya Kanade, Navin Goyal, Shuvendu K. Lahiri, Sriram K. Rajamani:
Guiding Language Models of Code with Global Context using Monitors. CoRR abs/2306.10763 (2023) - [i19]Naman Jain, Shubham Gandhi, Atharv Sonwane, Aditya Kanade, Nagarajan Natarajan, Suresh Parthasarathy, Sriram K. Rajamani, Rahul Sharma:
StaticFixer: From Static Analysis to Static Repair. CoRR abs/2307.12465 (2023) - [i18]Ramakrishna Bairi, Atharv Sonwane, Aditya Kanade, Vageesh D. C., Arun Iyer, Suresh Parthasarathy, Sriram K. Rajamani, Balasubramanyan Ashok, Shashank Shet:
CodePlan: Repository-level Coding using LLMs and Planning. CoRR abs/2309.12499 (2023) - [i17]Nalin Wadhwa, Jui Pradhan, Atharv Sonwane, Surya Prakash Sahu, Nagarajan Natarajan, Aditya Kanade, Suresh Parthasarathy, Sriram K. Rajamani:
Frustrated with Code Quality Issues? LLMs can Help! CoRR abs/2309.12938 (2023) - 2022
- [c30]Aditya Kanade, Mansi Sharma, Manivannan Muniyandi:
Tele-EvalNet: A Low-Cost, Teleconsultation System for Home Based Rehabilitation of Stroke Survivors Using Multiscale CNN-ConvLSTM Architecture. ECCV Workshops (6) 2022: 738-750 - [c29]Aditya Kanade:
Automating Software Engineering with Machine Learning. ISEC 2022: 1:1 - [i16]Aditya Kanade, Mansi Sharma, Manivannan Muniyandi:
A Robust and Scalable Attention Guided Deep Learning Framework for Movement Quality Assessment. CoRR abs/2204.07840 (2022) - [i15]Surya Prakash Sahu, Madhurima Mandal, Shikhar Bharadwaj, Aditya Kanade, Petros Maniatis, Shirish K. Shevade:
Learning to Answer Semantic Queries over Code. CoRR abs/2209.08372 (2022) - [i14]Ravi Raja, Stanly Samuel, Chiranjib Bhattacharyya, Deepak D'Souza, Aditya Kanade:
BNSynth: Bounded Boolean Functional Synthesis. CoRR abs/2212.08170 (2022) - 2021
- [i13]Soham Pal, Yash Gupta, Aditya Kanade, Shirish K. Shevade:
Stateful Detection of Model Extraction Attacks. CoRR abs/2107.05166 (2021) - [i12]Aditya Kanade, Mansi Sharma, M. Manivannan:
Tele-EvalNet: A Low-cost, Teleconsultation System for Home based Rehabilitation of Stroke Survivors using Multiscale CNN-LSTM Architecture. CoRR abs/2112.03168 (2021) - 2020
- [c28]Soham Pal, Yash Gupta, Aditya Shukla, Aditya Kanade, Shirish K. Shevade, Vinod Ganapathy:
ActiveThief: Model Extraction Using Active Learning and Unannotated Public Data. AAAI 2020: 865-872 - [c27]Aditya Kanade, Petros Maniatis, Gogul Balakrishnan, Kensen Shi:
Learning and Evaluating Contextual Embedding of Source Code. ICML 2020: 5110-5121 - [i11]Aditya Kanade, Petros Maniatis, Gogul Balakrishnan, Kensen Shi:
Pre-trained Contextual Embedding of Source Code. CoRR abs/2001.00059 (2020)
2010 – 2019
- 2019
- [j4]Aditya Kanade:
Chapter Seven - Event-Based Concurrency: Applications, Abstractions, and Analyses. Adv. Comput. 112: 379-412 (2019) - [c26]Rahul Gupta, Aditya Kanade, Shirish K. Shevade:
Deep Reinforcement Learning for Syntactic Error Repair in Student Programs. AAAI 2019: 930-937 - [c25]Marko Vasic, Aditya Kanade, Petros Maniatis, David Bieber, Rishabh Singh:
Neural Program Repair by Jointly Learning to Localize and Repair. ICLR (Poster) 2019 - [c24]Rahul Gupta, Aditya Kanade, Shirish K. Shevade:
Neural Attribution for Semantic Bug-Localization in Student Programs. NeurIPS 2019: 11861-11871 - [i10]Marko Vasic, Aditya Kanade, Petros Maniatis, David Bieber, Rishabh Singh:
Neural Program Repair by Jointly Learning to Localize and Repair. CoRR abs/1904.01720 (2019) - [i9]Soham Pal, Yash Gupta, Aditya Shukla, Aditya Kanade, Shirish K. Shevade, Vinod Ganapathy:
A framework for the extraction of Deep Neural Networks by leveraging public data. CoRR abs/1905.09165 (2019) - [i8]Rahul Gupta, Aditya Kanade, Shirish K. Shevade:
Deep Learning for Bug-Localization in Student Programs. CoRR abs/1905.12454 (2019) - 2018
- [c23]Ishan Rastogi, Aditya Kanade, Shirish K. Shevade:
Active Learning for Efficient Testing of Student Programs. AIED (2) 2018: 296-300 - [i7]Rahul Gupta, Aditya Kanade, Shirish K. Shevade:
Deep Reinforcement Learning for Programming Language Correction. CoRR abs/1801.10467 (2018) - [i6]Ishan Rastogi, Aditya Kanade, Shirish K. Shevade:
Active Learning for Efficient Testing of Student Programs. CoRR abs/1804.05655 (2018) - [i5]Ketan Patil, Aditya Kanade:
Greybox fuzzing as a contextual bandits problem. CoRR abs/1806.03806 (2018) - 2017
- [c22]Rahul Gupta, Soham Pal, Aditya Kanade, Shirish K. Shevade:
DeepFix: Fixing Common C Language Errors by Deep Learning. AAAI 2017: 1345-1351 - [c21]Pallavi Maiya, Aditya Kanade:
Efficient computation of happens-before relation for event-driven programs. ISSTA 2017: 102-112 - [c20]Anirudh Santhiar, Aditya Kanade:
Static deadlock detection for asynchronous C# programs. PLDI 2017: 292-305 - 2016
- [c19]Anirudh Santhiar, Shalini Kaleeswaran, Aditya Kanade:
Efficient race detection in the presence of programmatic event loops. ISSTA 2016: 366-376 - [c18]Ashish Mishra, Aditya Kanade, Y. N. Srikant:
Asynchrony-aware static analysis of Android applications. MEMOCODE 2016: 163-172 - [c17]Shalini Kaleeswaran, Anirudh Santhiar, Aditya Kanade, Sumit Gulwani:
Semi-supervised verified feedback generation. SIGSOFT FSE 2016: 739-750 - [c16]Pallavi Maiya, Rahul Gupta, Aditya Kanade, Rupak Majumdar:
Partial Order Reduction for Event-Driven Multi-threaded Programs. TACAS 2016: 680-697 - [i4]Shalini Kaleeswaran, Anirudh Santhiar, Aditya Kanade, Sumit Gulwani:
Semi-Supervised Verified Feedback Generation. CoRR abs/1603.04584 (2016) - 2015
- [j3]Jay Thakkar, Aditya Kanade:
Non-deterministic transducer models of retransmission protocols over noisy channels. Inf. Process. Lett. 115(9): 694-698 (2015) - [c15]Ivan Gavran, Filip Niksic, Aditya Kanade, Rupak Majumdar, Viktor Vafeiadis:
Rely/Guarantee Reasoning for Asynchronous Programs. CONCUR 2015: 483-496 - [c14]Mohammed Afraz, Diptikalyan Saha, Aditya Kanade:
P3: partitioned path profiling. ESEC/SIGSOFT FSE 2015: 485-495 - [i3]Pallavi Maiya, Rahul Gupta, Aditya Kanade, Rupak Majumdar:
A Partial Order Reduction Technique for Event-driven Multi-threaded Programs. CoRR abs/1511.03213 (2015) - 2014
- [j2]Anirudh Santhiar, Omesh Pandita, Aditya Kanade:
Mining Unit Tests for Discovery and Migration of Math APIs. ACM Trans. Softw. Eng. Methodol. 24(1): 4:1-4:33 (2014) - [c13]Shalini Kaleeswaran, Varun Tulsian, Aditya Kanade, Alessandro Orso:
MintHint: automated synthesis of repair hints. ICSE 2014: 266-276 - [c12]Varun Tulsian, Aditya Kanade, Rahul Kumar, Akash Lal, Aditya V. Nori:
MUX: algorithm selection for software model checkers. MSR 2014: 132-141 - [c11]Pallavi Maiya, Aditya Kanade, Rupak Majumdar:
Race detection for Android applications. PLDI 2014: 316-325 - 2013
- [c10]Anirudh Santhiar, Omesh Pandita, Aditya Kanade:
Discovering Math APIs by Mining Unit Tests. FASE 2013: 327-342 - [c9]Jay Thakkar, Aditya Kanade, Rajeev Alur:
Transducer-Based Algorithmic Verification of Retransmission Protocols over Noisy Channels. FMOODS/FORTE 2013: 209-224 - [i2]Shalini Kaleeswaran, Varun Tulsian, Aditya Kanade, Alessandro Orso:
MintHint: Automated Synthesis of Repair Hints. CoRR abs/1306.1286 (2013) - 2012
- [c8]Pranavadatta Devaki, Aditya Kanade:
Static Analysis for Checking Data Format Compatibility of Programs. FSTTCS 2012: 522-533 - [i1]Aditya Kanade, Amitabha Sanyal, Uday P. Khedker:
A Logic for Correlating Temporal Properties across Program Transformations. CoRR abs/1209.5152 (2012) - 2010
- [c7]Aditya Kanade, Rajeev Alur, Sriram K. Rajamani, Ganesan Ramalingam:
Representation dependence testing using program inversion. SIGSOFT FSE 2010: 277-286
2000 – 2009
- 2009
- [j1]Aditya Kanade, Amitabha Sanyal, Uday P. Khedker:
Validation of GCC optimizers through trace generation. Softw. Pract. Exp. 39(6): 611-639 (2009) - [c6]Aditya Kanade, Rajeev Alur, Franjo Ivancic, S. Ramesh, Sriram Sankaranarayanan, K. C. Shashidhar:
Generating and Analyzing Symbolic Traces of Simulink/Stateflow Models. CAV 2009: 430-445 - 2008
- [c5]Rajeev Alur, Aditya Kanade, Gera Weiss:
Ranking Automata and Games for Prioritized Requirements. CAV 2008: 240-253 - [c4]Rajeev Alur, Aditya Kanade, S. Ramesh, K. C. Shashidhar:
Symbolic analysis for improving simulation coverage of Simulink/Stateflow models. EMSOFT 2008: 89-98 - 2006
- [c3]Aditya Kanade, Amitabha Sanyal, Uday P. Khedker:
A PVS Based Framework for Validating Compiler Optimizations. SEFM 2006: 108-117 - [c2]Aditya Kanade, Amitabha Sanyal, Uday P. Khedker:
Structuring Optimizing Transformations and Proving Them Sound. COCV@ETAPS 2006: 79-95 - 2005
- [c1]Aditya Kanade, Uday P. Khedker, Amitabha Sanyal:
Heterogeneous Fixed Points with Application to Points-To Analysis. APLAS 2005: 298-314
Coauthor Index
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last updated on 2024-10-07 21:19 CEST by the dblp team
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