Leveraging Generative AI for Accelerating Enterprise Application Development: Insights from ChatGPT

Enterprise application development faces significant challenges, with each phase of the software development life cycle (SDLC) requiring experts with specific skills. The expertise of the individuals involved, greatly affects the quality and speed of work in each phase. The large size and complexity of modern software systems further exacerbates these problems. Recently, there has been a growing interest in using Generative AI (GenAI) techniques for software engineering tasks. GenAI can help Subject Matter Experts (SMEs) work more efficiently and can help in overcoming skill barriers. By leveraging GenAI, SMEs can save significant time and effort. This paper introduces meta-model based prompting approach to generate enterprise application code leveraging large language models (LLMs). Prompts help in the refinement of input requirements into refined requirements and design specifications using LLMs, ultimately generating code from these specifications. We share our approach and results of applying approach to generate small yet complex applications.

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Publication Details

Published
2024-12-03
DOI
https://doi.org/10.1109/apsec65559.2024.00052
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
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article

Leveraging Generative AI for Accelerating Enterprise Application Development: Insights from ChatGPT

Asha Rajbhoj, Vinay Kulkarni, Akanksha Somase, Tanay Sant
Big Data and Business Intelligence
article

Leveraging Generative AI for Accelerating Enterprise Application Development: Insights from ChatGPT

Asha Rajbhoj, Vinay Kulkarni, Akanksha Somase, Tanay Sant
article en

Abstract

Enterprise application development faces significant challenges, with each phase of the software development life cycle (SDLC) requiring experts with specific skills. The expertise of the individuals involved, greatly affects the quality and speed of work in each phase. The large size and complexity of modern software systems further exacerbates these problems. Recently, there has been a growing interest in using Generative AI (GenAI) techniques for software engineering tasks. GenAI can help Subject Matter Experts (SMEs) work more efficiently and can help in overcoming skill barriers. By leveraging GenAI, SMEs can save significant time and effort. This paper introduces meta-model based prompting approach to generate enterprise application code leveraging large language models (LLMs). Prompts help in the refinement of input requirements into refined requirements and design specifications using LLMs, ultimately generating code from these specifications. We share our approach and results of applying approach to generate small yet complex applications.

Tata Consultancy Services (India) (IN)
Industry, innovation and infrastructure
Openalex Percentile: Top 53%
Big Data and Business Intelligence
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