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

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arxiv 2406.05409 v1 pith:ZPU3ITQW submitted 2024-06-08 cs.SE cs.AIcs.PL

classification cs.SEcs.AIcs.PL
keywords softwarenaturalnlopprogramminglanguagecreationdemocratizingdevelopment
verification ladder T0 review T1 audit T2 compute T3 formal
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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.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. The Impact of Generative AI on Student Churn and the Future of Formal Education

    cs.IR 2024-11 reject novelty 2.0 of 10

    The paper asserts a trend of students abandoning degrees for AI-powered entrepreneurship but provides no quantitative evidence from its claimed social media analysis.

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