From Idea to Implementation: Evaluating the Influence of Large Language Models in Software Development—An Opinion Paper

Yadav, Sargam, Qureshi, Asifa Mehmood, Kaushik, Abhishek, ..., -, Singh, Nikhil Kumar and et al., - (2026) From Idea to Implementation: Evaluating the Influence of Large Language Models in Software Development—An Opinion Paper. Applied AI Letters, 7 (3). ISSN 26895595

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Abstract

The introduction of transformer architecture was a turning point in natural language processing (NLP). Models based on the transformer architecture, such as bidirectional encoder representations from transformers (BERT) and generative pretrained transformer (GPT), have gained widespread popularity in various applications such as software development and education. The availability of large language models (LLMs) such as ChatGPT and Bard to the general public has showcased the tremendous potential of these models and encouraged their integration into various domains such as software development, for tasks such as code generation, debugging, and documentation generation. In this study, opinions from 11 experts regarding their experience with LLMs for software development have been gathered and analyzed to draw insights that can guide successful and responsible integration. The overall opinion of the experts is positive, with the experts identifying advantages such as an increase in productivity and reduced coding time. Potential concerns and challenges such as risk of overdependence and ethical considerations have also been highlighted.

Item Type:	Article
Uncontrolled Keywords:	ChatGPT; coding; large language models; natural language generation; software development; transformer
Subjects:	P Language and Literature > P Philology. Linguistics > Computational linguistics. Natural language processing Q Science > QA Mathematics > Computer software > Computer software - Development T Technology > T Technology (General) > Information Technology > Computer software > Computer software - Development Q Science > QH Natural history > QH301 Biology > Methods of research. Technique. Experimental biology > Data processing. Bioinformatics > Artificial intelligence > Generative artificial intelligence Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Artificial intelligence > Generative artificial intelligence
Divisions:	School of Computing
Depositing User:	Tamara Malone
Date Deposited:	24 Jul 2026 11:34
Last Modified:	24 Jul 2026 11:34
URI:	https://norma.ncirl.ie/id/eprint/9479

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