Fetching the paper…
Reading the bibliography…
Rust is a programming language that combines memory safety and low-level control, providing C-like performance while guaranteeing the absence of undefined behaviors by default.
Few-shot parameter-efficient fine-tuning is better and cheaper than in-context learning
Haokun Liu, Derek Tam, Mohammed Muqeeth, Jay Mohta, Tenghao Huang, Mohit Bansal, and Colin A Raffel. 2022 · 1965
Earlier work this paper cites.
Provably-Safe
Jay Bosamiya, Wen Shih Lim, and Bryan Parno. 2022 · 1992
Earlier work this paper cites.
Property-based testing: a new approach to testing for assurance
George Fink and Matt Bishop. 1997 · 1997
Earlier work this paper cites.
Bounded model checking using satisfiability solving
Edmund Clarke, Armin Biere, Richard Raimi, and Yunshan Zhu. 2001 · 2001
Earlier work this paper cites.
A Tool for Checking ANSI-C Programs. In TACAS (LNCS, Vol. 2988) . Springer, 168–176
Edmund M. Clarke, Daniel Kroening, and Flavio Lerda. 2004 · 2004
Earlier work this paper cites.
Wilcoxon signed-rank test
Robert F Woolson. 2007 · 2007
Earlier work this paper cites.
Learning a Metric for Code Readability
Raymond P. L. Buse and Westley R. Weimer. 2010 · 2009
Earlier work this paper cites.
Code completion with statistical language models. In Proceedings of the 35th ACM SIGPLAN conference on programming language design and implementation . 419–428
Veselin Raychev, Martin Vechev, and Eran Yahav. 2014 · 2014
Earlier work this paper cites.
Program synthesis using natural language. In Proceedings of the 38th International Conference on Software Engineering . 345–356
Aditya Desai, Sumit Gulwani, Vineet Hingorani, Nidhi Jain, Amey Karkare, Mark Marron, and Subhajit Roy. 2016 · 2016
Earlier work this paper cites.
Awesome WebAssembly Languages
Stephen Akinyemi. 2023 · 2017
Earlier work this paper cites.
Sound Loop Superoptimization for Google Native Client
Berkeley Churchill, Rahul Sharma, JF Bastien, and Alex Aiken. 2017 · 2017
Earlier work this paper cites.
Black-Box Equivalence Checking Across Compiler Optimizations. In Programming Languages and Systems (LNCS) , Bor-Yuh Evan Chang (Ed.). Springer, 127–147
Manjeet Dahiya and Sorav Bansal. 2017 · 2017
Earlier work this paper cites.
Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin. 2017 · 2017
Earlier work this paper cites.
Semantic program alignment for equivalence checking. In Proceedings of the 40th ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI 2019) . Association for Computing Machinery, 1027–1040
Berkeley Churchill, Oded Padon, Rahul Sharma, and Alex Aiken. 2019 · 2019
Earlier work this paper cites.
Saturn-software deobfuscation framework based on llvm. In Proceedings of the 3rd ACM Workshop on Software Protection . 27–38
Peter Garba and Matteo Favaro. 2019 · 2019
Earlier work this paper cites.
How do programmers use unsafe rust?
Vytautas Astrauskas, Christoph Matheja, Federico Poli, Peter Müller, and Alexander J Summers. 2020 · 2020
Earlier work this paper cites.
Understanding and evolving the Rust programming language
Ralf Jung. 2020 · 2020
Earlier work this paper cites.
Wasim: Understanding webassembly applications through classification. In Proceedings of the 35th IEEE/ACM International Conference on Automated Software Engineering . 1321–1325
Alan Romano and Weihang Wang. 2020 · 2020
Earlier work this paper cites.
Unsupervised translation of programming languages
Baptiste Roziere, Marie-Anne Lachaux, Lowik Chanussot, and Guillaume Lample. 2020 · 2020
Cited alongside, same era.
SOAR: Synthesis for open-source API refactoring. In Companion Proceedings of the 2020 ACM SIGPLAN International Conference on Systems, Programming, Languages, and Applications: Software for Humanity . 10–12
Aidan ZH Yang. 2020 · 2020
Cited alongside, same era.
GPT-Neo: Large scale autoregressive language modeling with Mesh-Tensorflow
Sid Black, Leo Gao, Phil Wang, Connor Leahy, and Stella Biderman. 2021 · 2021
Cited alongside, same era.
Evaluating large language models trained on code
Mark Chen, Jerry Tworek, Heewoo Jun, Qiming Yuan, Henrique Ponde de Oliveira Pinto, Jared Kaplan, Harri Edwards, Yuri Burda, Nicholas Joseph, Greg Brockman, et al · 2021
Cited alongside, same era.
Translating C to safer Rust
Mehmet Emre, Ryan Schroeder, Kyle Dewey, and Ben Hardekopf. 2021 · 2021
Cited alongside, same era.
An Algebra of Alignment for Relational Verification
Timos Antonopoulos, Eric Koskinen, Ton Chanh Le, Ramana Nagasamudram, David A. Naumann, and Minh Ngo. 2023 · 2023
Later among the works it cites.
LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models
Zhiqiang Hu, Yihuai Lan, Lei Wang, Wanyu Xu, Ee-Peng Lim, Roy Ka-Wei Lee, Lidong Bing, and Soujanya Poria. 2023 · 2023
Later among the works it cites.
Why Choose Rust
Shashank Mohan Jain. 2023 · 2023
Later among the works it cites.
Self-supervised Learning to Prove Equivalence Between Straight-Line Programs via Rewrite Rules
Steve Kommrusch, Martin Monperrus, and Louis-Noël Pouchet. 2023 · 2023
Later among the works it cites.
Verus: Verifying Rust Programs using Linear Ghost Types
Andrea Lattuada, Travis Hance, Chanhee Cho, Matthias Brun, Isitha Subasinghe, Yi Zhou, Jon Howell, Bryan Parno, and Chris Hawblitzel. 2023 · 2023
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Soar: a synthesis approach for data science api refactoring. In 2021 IEEE/ACM 43rd International Conference on Software Engineering (ICSE) . IEEE, 112–124
Ansong Ni, Daniel Ramos, Aidan ZH Yang, Inês Lynce, Vasco Manquinho, Ruben Martins, and Claire Le Goues. 2021 · 2021
Cited alongside, same era.
An empirical cybersecurity evaluation of github copilot’s code contributions
Hammond Pearce, Baleegh Ahmad, Benjamin Tan, Brendan Dolan-Gavitt, and Ramesh Karri. 2021 · 2021
Cited alongside, same era.
Perfection not required? Human-AI partnerships in code translation. In 26th International Conference on Intelligent User Interfaces . 402–412
Justin D Weisz, Michael Muller, Stephanie Houde, John Richards, Steven I Ross, Fernando Martinez, Mayank Agarwal, and Kartik Talamadupula. 2021 · 2021
Cited alongside, same era.
Incoder: A generative model for code infilling and synthesis
Daniel Fried, Armen Aghajanyan, Jessy Lin, Sida Wang, Eric Wallace, Freda Shi, Ruiqi Zhong, Wen-tau Yih, Luke Zettlemoyer, and Mike Lewis. 2022 · 2022
Cited alongside, same era.
The stack: 3 TB of permissively licensed source code
Denis Kocetkov, Raymond Li, Loubna Ben Allal, Jia Li, Chenghao Mou, Carlos Muñoz Ferrandis, Yacine Jernite, Margaret Mitchell, Sean Hughes, Thomas Wolf, et al · 2022
Cited alongside, same era.
In Rust we trust: a transpiler from unsafe C to safer Rust. In Proceedings of the ACM/IEEE 44th International Conference on Software Engineering: Companion Proceedings . 354–355
Michael Ling, Yijun Yu, Haitao Wu, Yuan Wang, James R Cordy, and Ahmed E Hassan. 2022 · 2022
Cited alongside, same era.
CodeGen: An open large language model for code with multi-turn program synthesis
Erik Nijkamp, Bo Pang, Hiroaki Hayashi, Lifu Tu, Huan Wang, Yingbo Zhou, Silvio Savarese, and Caiming Xiong. 2022 · 2022
Cited alongside, same era.
Raymond Li, Loubna Ben Allal, Yangtian Zi, Niklas Muennighoff, Denis Kocetkov, Chenghao Mou, Marc Marone, Christopher Akiki, Jia Li, Jenny Chim, et al · 2023
Later among the works it cites.
Beyond Accuracy: Evaluating Self-Consistency of Code LLMs. In The Twelfth International Conference on Learning Representations
Marcus J Min, Yangruibo Ding, Luca Buratti, Saurabh Pujar, Gail Kaiser, Suman Jana, and Baishakhi Ray. 2023 · 2023
Later among the works it cites.
OpenAI. 2023 · 2023
Later among the works it cites.
Code llama: Open foundation models for code
Baptiste Roziere, Jonas Gehring, Fabian Gloeckle, Sten Sootla, Itai Gat, Xiaoqing Ellen Tan, Yossi Adi, Jingyu Liu, Tal Remez, Jérémy Rapin, et al · 2023
Later among the works it cites.
Llama: Open and efficient foundation language models
Hugo Touvron, Thibaut Lavril, Gautier Izacard, Xavier Martinet, Marie-Anne Lachaux, Timothée Lacroix, Baptiste Rozière, Naman Goyal, Eric Hambro, Faisal Azhar, et al · 2023
Later among the works it cites.
Leveraging Large Language Models for Automated Proof Synthesis in Rust
Jianan Yao, Ziqiao Zhou, Weiteng Chen, and Weidong Cui. 2023 · 2023
Later among the works it cites.
Ownership guided C to Rust translation. In Computer Aided Verification (CAV) (LNCS, Vol. 13966) . Springer, 459–482
Hanliang Zhang, Cristina David, Yijun Yu, and Meng Wang. 2023 · 2023
Later among the works it cites.
Emergent and predictable memorization in large language models
Stella Biderman, USVSN PRASHANTH, Lintang Sutawika, Hailey Schoelkopf, Quentin Anthony, Shivanshu Purohit, and Edward Raff. 2024 · 2024
Closest in time.
Lost in translation: A study of bugs introduced by large language models while translating code. In Proceedings of the IEEE/ACM 46th International Conference on Software Engineering . 1–13
Rangeet Pan, Ali Reza Ibrahimzada, Rahul Krishna, Divya Sankar, Lambert Pouguem Wassi, Michele Merler, Boris Sobolev, Raju Pavuluri, Saurabh Sinha, and Reyhaneh Jabbarvand. 2024 · 2024
Closest in time.
Integrating the future into the past: Approach to seamlessly integrate newly-developed Rust-components into an existing C++-system
Graf von Perponcher-Sedlnitzki and Philipp Christian. 2024 · 2024
Closest in time.
Hallucination is inevitable: An innate limitation of large language models
Ziwei Xu, Sanjay Jain, and Mohan Kankanhalli. 2024 · 2024
Closest in time.
Revisiting Unnaturalness for Automated Program Repair in the Era of Large Language Models
Aidan ZH Yang, Sophia Kolak, Vincent J Hellendoorn, Ruben Martins, and Claire Le Goues. 2024a · 2024
Closest in time.