Some things never change: how far generative AI can really change software engineering practice

TL;DR

This paper investigates the realistic impact of generative AI on software engineering, highlighting areas where it is expected to enhance productivity but not replace human expertise or creativity.

Contribution

It provides empirical insights from a survey on practitioners' expectations about GenAI's influence on various SE activities and compares these with existing roadmaps.

Findings

Practitioners expect increased productivity and quality from GenAI.

Some SE aspects like human expertise and creativity are not expected to change.

GenAI's usefulness may be limited in certain areas of software engineering.

Abstract

Generative Artificial Intelligence (GenAI) has become an emerging technology with the availability of several tools that could impact Software Engineering (SE) activities. As any other disruptive technology, GenAI led to the speculation that its full potential can deeply change SE. However, an overfocus on improving activities for which GenAI is more suitable could negligent other relevant areas of the process. In this paper, we aim to explore which SE activities are not expected to be profoundly changed by GenAI. To achieve this goal, we performed a survey with SE practitioners to identify their expectations regarding GenAI in SE, including impacts, challenges, ethical issues, and aspects they do not expect to change. We compared our results with previous roadmaps proposed in SE literature. Our results show that although practitioners expect an increase in productivity, coding, and process quality, they envision that some aspects will not change, such as the need for human expertise, creativity, and project management. Our results point to SE areas for which GenAI is probably not so useful, and future research could tackle them to improve SE practice.