ACIS 2024 Proceedings
Abstract
The software development industry faces numerous ongoing and increasing challenges, the most significant of which are the software development time and code quality. Reducing the development time without sacrificing code quality would significantly decrease overhead costs and improve the bottom line for Information Technology companies. This study investigates software developers’ perceptions and utilisation of Generative AI tools to address these challenges and improve the software development process. We employ a mixed-method approach to examine the impact of Gen AI tools on Software Development Time and Software Code Quality. We adopt semi-structured interviews with experienced software developers for qualitative study and administer a survey for quantitative research. Our study also examines how developers exploit the capabilities of Gen AI technologies in their professional endeavours, drawing on the principles of Delone & McLean Information System success model theory. The findings aim to elucidate the effective integration of Gen AI into software development processes, aiming to transform the sector by enhancing productivity and quality.
Recommended Citation
Subramanya, Srinivas and Paul, Anindita, "Promises and Pitfalls: Evaluating Generative AI Tools in Software Engineering" (2024). ACIS 2024 Proceedings. 69.
https://aisel.aisnet.org/acis2024/69