Impacts of the Usage of Generative Artificial Intelligence on Software Development Process

Context: Over the years, tools have been created to improve the execution of development process activities. The emergence of generative Artificial Intelligence (AI) and, more recently, the launch and dissemination of Copilot, ChatGPT-3 and other generative tools, have broadened the discussion about the possibility of using conversational generative AI tools in diverse development tasks. Problem: There is still a lack of secondary studies to map the literature about how software development process activities can be affected by the usage of generative AI tools. Solution: This study aims to identify in which activities of the software development process Natural Language (NL) generative AI tools have been used and how they can impact requirements specification, design/architecture, development and testing activities. IS Theory: The study was developed under the aegis of the Task Technology Fit theory. Method: This work presents the results of a Systematic Mapping Review (SMR) carried out to collect research results that investigate the application of generative AI tools in the software development process. Results: Results indicate that the main activities affected are development and testing and that, although there are still some issues to be addressed, there are benefits in using AI generative tools compared to using more traditional methods like human-human pair programming and code testing made by software engineering professionals. Contribution: It was possible to collect studies to identify in which activities of the software development process generative AI tools can be applied and what are the impacts of using this technology.