Forecasting Developer Environments with GenAI: A Research Perspective

Raula Gaikovina Kula, Christoph Treude, Xing Hu, Sebastian Baltes, Earl T. Barr, Kelly Blincoe, Fabio Calefato, Junjie Chen, Marc Cheong, Youmei Fan, Daniel M. German, Marco Gerosa, Jin Guo, Shinpei Hayashi, Robert Hirschfeld, Reid Holmes, Yintong Huo, Takashi Kobayashi, Michele Lanza, Zhongxin Liu, Olivier Nourry, Nicole Novielli, Denys Poshyvanyk, Shinobu Saito, Kazumasa Shimari, Igor Steinmacher, Mairieli Wessel, Markus Wagner, Annie Vella, Laurie Williams, Xin Xia

Generative Artificial Intelligence (GenAI) models are achieving remarkable performance in various tasks, including code generation, testing, code review, and program repair. The ability to increase the level of abstraction away from writing code has the potential to change the Human-AI interaction within the integrated development environment (IDE). To explore the impact of GenAI on IDEs, 33 experts from the Software Engineering, Artificial Intelligence, and Human-Computer Interaction domains gathered to discuss challenges and opportunities at Shonan Meeting 222, a four-day intensive research meeting. Four themes emerged as areas of interest to the researchers: to what extent the IDE will evolve to solve current problems, how the IDE can lead the charge for a new paradigm, how the human role will change, and radical ideas of how the IDE will look in the future.

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