Miltiadis Allamanis

According to our database, Miltiadis Allamanis authored at least 65 papers between 2012 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of four.

2024

Deep End-to-end Causal Inference.

Tomas Geffner, Javier Antorán, Adam Foster, Wenbo Gong, Chao Ma, Emre Kiciman, Amit Sharma, Angus Lamb, Martin Kukla, Nick Pawlowski, Agrin Hilmkil, Joel Jennings, Meyer Scetbon, Miltiadis Allamanis, Cheng Zhang

Trans. Mach. Learn. Res., 2024

Do Large Code Models Understand Programming Concepts? A Black-box Approach.

Ashish Hooda, Mihai Christodorescu, Miltiadis Allamanis, Aaron Wilson, Kassem Fawaz, Somesh Jha

CoRR, 2024

NExT: Teaching Large Language Models to Reason about Code Execution.

Ansong Ni, Miltiadis Allamanis, Arman Cohan, Yinlin Deng, Kensen Shi, Charles Sutton, Pengcheng Yin

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Do Large Code Models Understand Programming Concepts? Counterfactual Analysis for Code Predicates.

Ashish Hooda, Mihai Christodorescu, Miltiadis Allamanis, Aaron Wilson, Kassem Fawaz, Somesh Jha

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Unsupervised Evaluation of Code LLMs with Round-Trip Correctness.

Miltiadis Allamanis, Sheena Panthaplackel, Pengcheng Yin

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

DIRE and its Data: Neural Decompiled Variable Renamings with Respect to Software Class.

Luke Dramko, Jeremy Lacomis, Pengcheng Yin, Edward J. Schwartz, Miltiadis Allamanis, Graham Neubig, Bogdan Vasilescu, Claire Le Goues

ACM Trans. Softw. Eng. Methodol., April, 2023

JEMMA: An extensible Java dataset for ML4Code applications.

Anjan Karmakar, Miltiadis Allamanis, Romain Robbes

Empir. Softw. Eng., March, 2023

Epicure: Distilling Sequence Model Predictions into Patterns.

Miltiadis Allamanis, Earl T. Barr

CoRR, 2023

AdaptivePaste: Intelligent Copy-Paste in IDE.

Xiaoyu Liu, Jinu Jang, Neel Sundaresan, Miltiadis Allamanis, Alexey Svyatkovskiy

Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, 2023

2022

CODIT: Code Editing With Tree-Based Neural Models.

Saikat Chakraborty, Yangruibo Ding, Miltiadis Allamanis, Baishakhi Ray

IEEE Trans. Software Eng., 2022

HEAT: Hyperedge Attention Networks.

Dobrik Georgiev, Marc Brockschmidt, Miltiadis Allamanis

Trans. Mach. Learn. Res., 2022

Overwatch: learning patterns in code edit sequences.

Yuhao Zhang, Yasharth Bajpai, Priyanshu Gupta, Ameya Ketkar, Miltiadis Allamanis, Titus Barik, Sumit Gulwani, Arjun Radhakrishna, Mohammad Raza, Gustavo Soares, Ashish Tiwari

Proc. ACM Program. Lang., 2022

Embedding and classifying test execution traces using neural networks.

Foivos Tsimpourlas, Gwenyth Rooijackers, Ajitha Rajan, Miltiadis Allamanis

IET Softw., 2022

AdaptivePaste: Code Adaptation through Learning Semantics-aware Variable Usage Representations.

Xiaoyu Liu, Jinu Jang, Neel Sundaresan, Miltiadis Allamanis, Alexey Svyatkovskiy

CoRR, 2022

Is Surprisal in Issue Trackers Actionable?

James Caddy, Markus Wagner, Christoph Treude, Earl T. Barr, Miltiadis Allamanis

CoRR, 2022

Deep End-to-end Causal Inference.

Tomas Geffner, Javier Antorán, Adam Foster, Wenbo Gong, Chao Ma, Emre Kiciman, Amit Sharma, Angus Lamb, Martin Kukla, Nick Pawlowski, Miltiadis Allamanis, Cheng Zhang

CoRR, 2022

Simultaneous Missing Value Imputation and Structure Learning with Groups.

Pablo Morales-Alvarez, Wenbo Gong, Angus Lamb, Simon Woodhead, Simon Peyton Jones, Nick Pawlowski, Miltiadis Allamanis, Cheng Zhang

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

NS3: Neuro-symbolic Semantic Code Search.

Shushan Arakelyan, Anna Hakhverdyan, Miltiadis Allamanis, Luis Garcia, Christophe Hauser, Xiang Ren

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

CoRGi: Content-Rich Graph Neural Networks with Attention.

Jooyeon Kim, Angus Lamb, Simon Woodhead, Simon Peyton Jones, Cheng Zhang, Miltiadis Allamanis

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Learning to Complete Code with Sketches.

Daya Guo, Alexey Svyatkovskiy, Jian Yin, Nan Duan, Marc Brockschmidt, Miltiadis Allamanis

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

VICause: Simultaneous Missing Value Imputation and Causal Discovery with Groups.

Pablo Morales-Alvarez, Angus Lamb, Simon Woodhead, Simon Peyton Jones, Miltiadis Allamanis, Cheng Zhang

CoRR, 2021

CoRGi: Content-Rich Graph Neural Networks with Attention.

Jooyeon Kim, Angus Lamb, Simon Woodhead, Simon Peyton Jones, Cheng Zheng, Miltiadis Allamanis

CoRR, 2021

Learning to Generate Code Sketches.

Daya Guo, Alexey Svyatkovskiy, Jian Yin, Nan Duan, Marc Brockschmidt, Miltiadis Allamanis

CoRR, 2021

Supervised learning over test executions as a test oracle.

Foivos Tsimpourlas, Ajitha Rajan, Miltiadis Allamanis

Proceedings of the SAC '21: The 36th ACM/SIGAPP Symposium on Applied Computing, 2021

Self-Supervised Bug Detection and Repair.

Miltiadis Allamanis, Henry Jackson-Flux, Marc Brockschmidt

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Fast and Memory-Efficient Neural Code Completion.

Alexey Svyatkovskiy, Sebastian Lee, Anna Hadjitofi, Maik Riechert, Juliana Vicente Franco, Miltiadis Allamanis

Proceedings of the 18th IEEE/ACM International Conference on Mining Software Repositories, 2021

Copy That! Editing Sequences by Copying Spans.

Sheena Panthaplackel, Miltiadis Allamanis, Marc Brockschmidt

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Learning to Encode and Classify Test Executions.

Foivos Tsimpourlas, Ajitha Rajan, Miltiadis Allamanis

CoRR, 2020

Flexeme: untangling commits using lexical flows.

Profir-Petru Pârtachi, Santanu Kumar Dash, Miltiadis Allamanis, Earl T. Barr

Proceedings of the ESEC/FSE '20: 28th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, 2020

Typilus: neural type hints.

Miltiadis Allamanis, Earl T. Barr, Soline Ducousso, Zheng Gao

Proceedings of the 41st ACM SIGPLAN International Conference on Programming Language Design and Implementation, 2020

2019

Deduplication Index for Big Code Datasets.

Miltiadis Allamanis

Dataset, June, 2019

CodeSearchNet Challenge: Evaluating the State of Semantic Code Search.

Hamel Husain, Ho-Hsiang Wu, Tiferet Gazit, Miltiadis Allamanis, Marc Brockschmidt

CoRR, 2019

The adverse effects of code duplication in machine learning models of code.

Miltiadis Allamanis

Proceedings of the 2019 ACM SIGPLAN International Symposium on New Ideas, 2019

Program Synthesis and Semantic Parsing with Learned Code Idioms.

Eui Chul Richard Shin, Miltiadis Allamanis, Marc Brockschmidt, Alex Polozov

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

DIRE: A Neural Approach to Decompiled Identifier Naming.

Jeremy Lacomis, Pengcheng Yin, Edward J. Schwartz, Miltiadis Allamanis, Claire Le Goues, Graham Neubig, Bogdan Vasilescu

Proceedings of the 34th IEEE/ACM International Conference on Automated Software Engineering, 2019

Learning units-of-measure from scientific code.

Matthew Danish, Miltiadis Allamanis, Marc Brockschmidt, Andrew C. Rice, Dominic Orchard

Proceedings of the 14th International Workshop on Software Engineering for Science, 2019

Learning to Represent Edits.

Pengcheng Yin, Graham Neubig, Miltiadis Allamanis, Marc Brockschmidt, Alexander L. Gaunt

Proceedings of the 7th International Conference on Learning Representations, 2019

Structured Neural Summarization.

Patrick Fernandes, Miltiadis Allamanis, Marc Brockschmidt

Proceedings of the 7th International Conference on Learning Representations, 2019

Generative Code Modeling with Graphs.

Marc Brockschmidt, Miltiadis Allamanis, Alexander L. Gaunt, Oleksandr Polozov

Proceedings of the 7th International Conference on Learning Representations, 2019

2018

Mining Semantic Loop Idioms.

Miltiadis Allamanis, Earl T. Barr, Christian Bird, Premkumar T. Devanbu, Mark Marron, Charles Sutton

IEEE Trans. Software Eng., 2018

A Survey of Machine Learning for Big Code and Naturalness.

Miltiadis Allamanis, Earl T. Barr, Premkumar T. Devanbu, Charles Sutton

ACM Comput. Surv., 2018

Tree2Tree Neural Translation Model for Learning Source Code Changes.

Saikat Chakraborty, Miltiadis Allamanis, Baishakhi Ray

CoRR, 2018

Deep learning type inference.

Vincent J. Hellendoorn, Christian Bird, Earl T. Barr, Miltiadis Allamanis

Proceedings of the 2018 ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering, 2018

RefiNym: using names to refine types.

Santanu Kumar Dash, Miltiadis Allamanis, Earl T. Barr

Proceedings of the 2018 ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering, 2018

Constrained Graph Variational Autoencoders for Molecule Design.

Qi Liu, Miltiadis Allamanis, Marc Brockschmidt, Alexander L. Gaunt

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Modelling Natural Language, Programs, and their Intersection.

Graham Neubig, Miltiadis Allamanis

Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics, 2018

Learning to Represent Programs with Graphs.

Miltiadis Allamanis, Marc Brockschmidt, Mahmoud Khademi

Proceedings of the 6th International Conference on Learning Representations, 2018

2017

Learning natural coding conventions

Miltiadis Allamanis

PhD thesis, 2017

Autofolding for Source Code Summarization.

Jaroslav M. Fowkes, Pankajan Chanthirasegaran, Razvan Ranca, Miltiadis Allamanis, Mirella Lapata, Charles Sutton

IEEE Trans. Software Eng., 2017

SmartPaste: Learning to Adapt Source Code.

Miltiadis Allamanis, Marc Brockschmidt

CoRR, 2017

Learning Continuous Semantic Representations of Symbolic Expressions.

Miltiadis Allamanis, Pankajan Chanthirasegaran, Pushmeet Kohli, Charles Sutton

Proceedings of the 34th International Conference on Machine Learning, 2017

2016

Tailored Mutants Fit Bugs Better.

Miltiadis Allamanis, Earl T. Barr, René Just, Charles Sutton

CoRR, 2016

TASSAL: autofolding for source code summarization.

Jaroslav M. Fowkes, Pankajan Chanthirasegaran, Razvan Ranca, Miltiadis Allamanis, Mirella Lapata, Charles Sutton

Proceedings of the 38th International Conference on Software Engineering, 2016

A Convolutional Attention Network for Extreme Summarization of Source Code.

Miltiadis Allamanis, Hao Peng, Charles Sutton

Proceedings of the 33nd International Conference on Machine Learning, 2016

2015

Inducing Generalized Multi-Label Rules with Learning Classifier Systems.

Fani A. Tzima, Miltiadis Allamanis, Alexandros Filotheou, Pericles A. Mitkas

CoRR, 2015

Suggesting accurate method and class names.

Miltiadis Allamanis, Earl T. Barr, Christian Bird, Charles Sutton

Proceedings of the 2015 10th Joint Meeting on Foundations of Software Engineering, 2015

Bimodal Modelling of Source Code and Natural Language.

Miltiadis Allamanis, Daniel Tarlow, Andrew D. Gordon, Yi Wei

Proceedings of the 32nd International Conference on Machine Learning, 2015

2014

Autofolding for Source Code Summarization.

Jaroslav M. Fowkes, Razvan Ranca, Miltiadis Allamanis, Mirella Lapata, Charles Sutton

CoRR, 2014

Learning Natural Coding Conventions.

Miltiadis Allamanis, Earl T. Barr, Charles Sutton

CoRR, 2014

Mining idioms from source code.

Miltiadis Allamanis, Charles Sutton

Proceedings of the 22nd ACM SIGSOFT International Symposium on Foundations of Software Engineering, (FSE-22), Hong Kong, China, November 16, 2014

Learning natural coding conventions.

Miltiadis Allamanis, Earl T. Barr, Christian Bird, Charles Sutton

Proceedings of the 22nd ACM SIGSOFT International Symposium on Foundations of Software Engineering, (FSE-22), Hong Kong, China, November 16, 2014

2013

Mining source code repositories at massive scale using language modeling.

Miltiadis Allamanis, Charles Sutton

Proceedings of the 10th Working Conference on Mining Software Repositories, 2013

Why, when, and what: analyzing stack overflow questions by topic, type, and code.

Miltiadis Allamanis, Charles Sutton

Proceedings of the 10th Working Conference on Mining Software Repositories, 2013

Effective Rule-Based Multi-label Classification with Learning Classifier Systems.

Miltiadis Allamanis, Fani A. Tzima, Pericles A. Mitkas

Proceedings of the Adaptive and Natural Computing Algorithms, 2013

2012

Evolution of a location-based online social network: analysis and models.

Miltiadis Allamanis, Salvatore Scellato, Cecilia Mascolo

Proceedings of the 12th ACM SIGCOMM Internet Measurement Conference, 2012