NAPS: Natural Program Synthesis Dataset
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Abstract (arXiv)
We present a program synthesis-oriented dataset consisting of human written problem statements and solutions for these problems. The problem statements were collected via crowdsourcing and the program solutions were extracted from human-written solutions in programming competitions, accompanied by input/output examples. We propose using this dataset for the program synthesis tasks aimed for working with real user-generated data. As a baseline we present few models, with the best model achieving 8.8% accuracy, showcasing both the complexity of the dataset and large room for future research.
Key facts. Cited by 14 papers in the map (data through 7 Oct 2026). First posted on arXiv 6 Jul 2018.
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Citing papers per year: 2021: 4; 2022: 4; 2023: 1; 2024: 3; 2025: 2.
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- 2021Program Synthesis with Large Language Modelscited by 3,509
- 2021Measuring Coding Challenge Competence With APPScited by 879
- 2022Language Models Can Teach Themselves to Program Bettercited by 75
- 2022Execution-based Evaluation for Data Science Code Generation Modelscited by 31
- 2023Fully Autonomous Programming with Large Language Modelscited by 31
- 2021Programming Puzzlescited by 25
- 2024Efficacy of Various Large Language Models in Generating Smart Contractscited by 4
- 2021On Adversarial Robustness of Synthetic Code Generationcited by 3
- 2022A Survey on Artificial Intelligence for Source Code: A Dialogue Systems Perspectivecited by 3
- 2024RoCode: A Dataset for Measuring Code Intelligence from Problem Definitions in Romaniancited by 3
- 2025Benchmarking AI Models in Software Engineering: A Review, Search Tool, and Unified Approach for Elevating Benchmark Qualitycited by 3
- 2025Fully Autonomous Programming using Iterative Multi-Agent Debugging with Large Language Modelscited by 3
2 more
- 2022JEMMA: An Extensible Java Dataset for ML4Code Applicationscited by 2
- 2024Generating Unseen Code Tests In Infinitumcited by 0
- 2025Fully Autonomous Programming using Iterative Multi-Agent Debugging with Large Language Models10 Mar 2025
- 2025Benchmarking AI Models in Software Engineering: A Review, Search Tool, and Unified Approach for Elevating Benchmark Quality7 Mar 2025
- 2024Generating Unseen Code Tests In Infinitum29 Jul 2024
- 2024Efficacy of Various Large Language Models in Generating Smart Contracts28 Jun 2024
- 2024RoCode: A Dataset for Measuring Code Intelligence from Problem Definitions in Romanian20 Feb 2024
- 2023Fully Autonomous Programming with Large Language Models20 Apr 2023
- 2022JEMMA: An Extensible Java Dataset for ML4Code Applications18 Dec 2022
- 2022Execution-based Evaluation for Data Science Code Generation Models17 Nov 2022
- 2022Language Models Can Teach Themselves to Program Better29 Jul 2022
- 2022A Survey on Artificial Intelligence for Source Code: A Dialogue Systems Perspective10 Feb 2022
- 2021Program Synthesis with Large Language Models16 Aug 2021
- 2021On Adversarial Robustness of Synthetic Code Generation22 Jun 2021
2 more
- 2021Programming Puzzles10 Jun 2021
- 2021Measuring Coding Challenge Competence With APPS20 May 2021
- 2021Program Synthesis with Large Language Modelscited by 3,509
- 2021Measuring Coding Challenge Competence With APPScited by 879
- 2022Language Models Can Teach Themselves to Program Bettercited by 75
- 2022Execution-based Evaluation for Data Science Code Generation Modelscited by 31
- 2023Fully Autonomous Programming with Large Language Modelscited by 31
- 2021Programming Puzzlescited by 25
- 2024Efficacy of Various Large Language Models in Generating Smart Contractscited by 4
- 2021On Adversarial Robustness of Synthetic Code Generationcited by 3
- 2022A Survey on Artificial Intelligence for Source Code: A Dialogue Systems Perspectivecited by 3
- 2024RoCode: A Dataset for Measuring Code Intelligence from Problem Definitions in Romaniancited by 3
- 2025Benchmarking AI Models in Software Engineering: A Review, Search Tool, and Unified Approach for Elevating Benchmark Qualitycited by 3
- 2022JEMMA: An Extensible Java Dataset for ML4Code Applicationscited by 2
12 most cited of 13 All 13 (JSON)
- 2025Benchmarking AI Models in Software Engineering: A Review, Search Tool, and Unified Approach for Elevating Benchmark Quality7 Mar 2025
- 2024Generating Unseen Code Tests In Infinitum29 Jul 2024
- 2024Efficacy of Various Large Language Models in Generating Smart Contracts28 Jun 2024
- 2024RoCode: A Dataset for Measuring Code Intelligence from Problem Definitions in Romanian20 Feb 2024
- 2023Fully Autonomous Programming with Large Language Models20 Apr 2023
- 2022JEMMA: An Extensible Java Dataset for ML4Code Applications18 Dec 2022
- 2022Execution-based Evaluation for Data Science Code Generation Models17 Nov 2022
- 2022Language Models Can Teach Themselves to Program Better29 Jul 2022
- 2022A Survey on Artificial Intelligence for Source Code: A Dialogue Systems Perspective10 Feb 2022
- 2021Program Synthesis with Large Language Models16 Aug 2021
- 2021On Adversarial Robustness of Synthetic Code Generation22 Jun 2021
- 2021Programming Puzzles10 Jun 2021
12 newest of 13 All 13 (JSON)