Lessons Learned from the Use of Generative AI in Engineering and Quality Assurance of a WEB System for Healthcare

TL;DR

This paper shares lessons learned from integrating Generative AI into the development and quality assurance of a healthcare web system, highlighting early insights and practical experiences.

Contribution

It provides an experiential report on applying Generative AI in software engineering processes within a healthcare context, an area with limited prior documented experiences.

Findings

Generative AI can support various software development activities.

Early results suggest potential benefits but lack conclusive evidence.

Insights can guide organizations adopting AI in software quality assurance.

Abstract

The advances and availability of technologies involving Generative Artificial Intelligence (AI) are evolving clearly and explicitly, driving immediate changes in various work activities. Software Engineering (SE) is no exception and stands to benefit from these new technologies, enhancing productivity and quality in its software development processes. However, although the use of Generative AI in SE practices is still in its early stages, considering the lack of conclusive results from ongoing research and the limited technological maturity, we have chosen to incorporate these technologies in the development of a web-based software system to be used in clinical trials by a thoracic diseases research group at our university. For this reason, we decided to share this experience report documenting our development team's learning journey in using Generative AI during the software development process. Project management, requirements specification, design, development, and quality assurance activities form the scope of observation. Although we do not yet have definitive technological evidence to evolve our development process significantly, the results obtained and the suggestions shared here represent valuable insights for software organizations seeking to innovate their development practices to achieve software quality with generative AI.