mlsanityData to 7 Oct 2026

Natural Language-Oriented Programming (NLOP): Towards Democratizing Software Creation

arXiv 2406.05409 ↗First posted 8 Jun 2024cs.SE cs.AI cs.PLcited by 4

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Abstract (arXiv)

As generative Artificial Intelligence (AI) technologies evolve, they offer unprecedented potential to automate and enhance various tasks, including coding. Natural Language-Oriented Programming (NLOP), a vision introduced in this paper, harnesses this potential by allowing developers to articulate software requirements and logic in their natural language, thereby democratizing software creation. This approach streamlines the development process and significantly lowers the barrier to entry for software engineering, making it feasible for non-experts to contribute effectively to software projects. By simplifying the transition from concept to code, NLOP can accelerate development cycles, enhance collaborative efforts, and reduce misunderstandings in requirement specifications. This paper reviews various programming models, assesses their contributions and limitations, and highlights that natural language will be the new programming language. Through this comparison, we illustrate how NLOP stands to transform the landscape of software engineering by fostering greater inclusivity and innovation.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Builds on 6 of its 15 references that are in the map. First posted on arXiv 8 Jun 2024.

Builds on

6 of 15 references.

References · 6

  1. 2017Attention Is All You Needcited by 59,932
  2. 2021On the Opportunities and Risks of Foundation Modelscited by 3,961
  3. 2023A Survey on Evaluation of Large Language Modelscited by 1,227
  4. 2017Generative Adversarial Networks: An Overviewcited by 588
  5. 2023From Copilot to Pilot: Towards AI Supported Software Developmentcited by 14
  6. 2023ProcessGPT: Transforming Business Process Management with Generative Artificial Intelligencecited by 11

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 2; 2026: 2.

4 papers.