--- title: "Code & programming languages — papers, page 2" description: "Code & programming languages: 42 papers of the Elamur Research library · page 2 of 2 · 26–42, the most cited first." canonical: "https://research.elamur.ai/free/en/topics/code-and-programming/page/2/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/topics/code-and-programming/page/2/) [home](https://md.research.elamur.ai/free/en/) / [topics](https://md.research.elamur.ai/free/en/topics/) / [Code & programming languages](https://md.research.elamur.ai/free/en/topics/code-and-programming/) / page 2 # 💻 Code & programming languages 42 papers · page 2 of 2 · 26–42 · the most cited first · [all topics](https://md.research.elamur.ai/free/en/topics/) Programs as text: code generation, program synthesis and the languages programs are written in. [← prev](https://md.research.elamur.ai/free/en/topics/code-and-programming/) [1](https://md.research.elamur.ai/free/en/topics/code-and-programming/) **2** 26. [**AlphaEvolve: A coding agent for scientific and algorithmic discovery**Alexander Novikov, Ngân Vũ, Marvin Eisenberger, et al.*2025 · 176 citations*](https://md.research.elamur.ai/free/en/papers/novikov-2025-alphaevolve-coding-agent-scientific-algorithmic/) 27. [**Structure-Grounded Pretraining for Text-to-SQL**Xiang Deng, Ahmed Hassan Awadallah, Christopher Meek, et al.*2021 · 166 citations*](https://md.research.elamur.ai/free/en/papers/deng-2021-structure-grounded-pretraining-text-sql/) 28. [**BigCodeBench: Benchmarking Code Generation with Diverse Function Calls and Complex Instructions**Terry Yue Zhuo, Minh Chien Vu, Jenny Chim, et al.*2024 · 163 citations*](https://md.research.elamur.ai/free/en/papers/zhuo-2024-bigcodebench-benchmarking-code-generation-diverse/) 29. [**Unsupervised Translation of Programming Languages**Marie-Anne Lachaux, Baptiste Roziere, Lowik Chanussot, et al.*2020 · 156 citations*](https://md.research.elamur.ai/free/en/papers/lachaux-2020-unsupervised-translation-programming-languages/) 30. [**The Lean 4 Theorem Prover and Programming Language (System Description)**Leonardo de Moura, Sebastian Ullrich*2021 · 150 citations*](https://md.research.elamur.ai/free/en/papers/moura-2021-lean-4-theorem-prover-programming/) 31. [**LEVER: Learning to Verify Language-to-Code Generation with Execution**Ansong Ni, Srini Iyer, Dragomir Radev, et al.*2023 · 122 citations*](https://md.research.elamur.ai/free/en/papers/ni-2023-lever-learning-verify-language-code/) 32. [**DuSQL: A Large-Scale and Pragmatic Chinese Text-to-SQL Dataset**Lijie Wang, Ao Zhang, Kun Wu, et al.*2020 · 63 citations*](https://md.research.elamur.ai/free/en/papers/wang-2020-dusql-large-scale-pragmatic-chinese/) 33. [**TigerCoder: A Novel Suite of LLMs for Code Generation in Bangla**Nishat Raihan, Antonios Anastasopoulos, Marcos Zampieri*2026 · 13 citations*](https://md.research.elamur.ai/free/en/papers/raihan-2026-tigercoder-novel-suite-llms-code/) 34. [**Ar-Spider: Text-to-SQL in Arabic**Saleh Almohaimeed, Saad Almohaimeed, Mansour Al Ghanim, et al.*2024 · 13 citations*](https://md.research.elamur.ai/free/en/papers/almohaimeed-2024-ar-spider-text-sql-arabic/) 35. [**Prompt Engineering Techniques for Context-dependent Text-to-SQL in Arabic**Saleh Almohaimeed, May Alsofyani, Saad Almohaimeed, et al.*2025 · 2 citations*](https://md.research.elamur.ai/free/en/papers/almohaimeed-2025-prompt-engineering-techniques-context-dependent/) 36. [**Synthetic Function Demonstrations Improve Generation in Low-Resource Programming Languages**Nick McKenna, Xinnuo Xu, Jack Williams, et al.*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/mckenna-2026-synthetic-function-demonstrations-improve-generation/) 37. [**Research Progress of Pre-trained Model in Software Engineering (预训练模型在软件工程领域应用研究进展)**Lina Gong (宫丽娜), Yiren Zhou (周易人), Yu Qiao (乔羽), et al.*2024 · 1 citation*](https://md.research.elamur.ai/free/en/papers/gong-2024-pre-trained-model/) 38. [**Deep Learning Based Code Generation Methods: Literature Review (基于深度学习的代码生成方法研究进展)**Zezhou Yang (杨泽洲), Sirong Chen (陈思榕), Cuiyun Gao (高翠芸), et al.*2023 · 1 citation*](https://md.research.elamur.ai/free/en/papers/yang-2023-deep-learning-code/) 39. [**Survey of Large-Language-Model-Based Automated Program Repair (基于大语言模型的自动代码修复综述)**Pengyu Xu (许鹏宇), Boyu Kuang (况博裕), Mang Su (苏铓), et al.*2025*](https://md.research.elamur.ai/free/en/papers/xu-2025-large-language-model/) 40. [**Survey on Application of Retrieval-augmented Generation in Software Engineering (检索增强生成在软件工程中的应用综述)**Quanjun Zhang (张犬俊), Yang Xie (谢杨), Chunrong Fang (房春荣), et al.*2025*](https://md.research.elamur.ai/free/en/papers/zhang-2025-application-retrieval-augmented/) 41. [**Survey on Code Generation with LLM-based Agents (基于大语言模型智能体的代码生成综述)**Yihong Dong (董益宏), Xue Jiang (姜雪), Jiaru Qian (钱家如), et al.*2025*](https://md.research.elamur.ai/free/en/papers/dong-2025-code-generation-llm/) 42. [**LLMs as Compiler for Arabic Programming Language**Serry Sibaee, Omar Najar, Lahouri Ghouti, et al.*2024*](https://md.research.elamur.ai/free/en/papers/sibaee-2024-llms-compiler-arabic-programming-language/) [← prev](https://md.research.elamur.ai/free/en/topics/code-and-programming/) [1](https://md.research.elamur.ai/free/en/topics/code-and-programming/) **2**