Model-based Maintenance and Evolution with GenAI: A Look into the Future
<|reference_start|>Model-based Maintenance and Evolution with GenAI: A Look into the Future: Model-Based Engineering (MBE) has streamlined software development by focusing on abstraction and automation. The adoption of MBE in Maintenance and Evolution (MBM&E), however, is still limited due to poor tool support and a lack of perceived benefits. We argue that Generative Artificial Intelligence (GenAI) can be used as a means to address the limitations of MBM&E. In this sense, we argue that GenAI, driven by Foundation Models, offers promising potential for enhancing MBM&E tasks. With this possibility in mind, we introduce a research vision that contains a classification scheme for GenAI approaches in MBM&E considering two main aspects: (i) the level of augmentation provided by GenAI and (ii) the experience of the engineers involved. We propose that GenAI can be used in MBM&E for: reducing engineers' learning curve, maximizing efficiency with recommendations, or serving as a reasoning tool to understand domain problems. Furthermore, we outline challenges in this field as a research agenda to drive scientific and practical future solutions. With this proposed vision, we aim to bridge the gap between GenAI and MBM&E, presenting a structured and sophisticated way for advancing MBM&E practices.<|reference_end|>
@article{marchezan2024model-based,
    title={Model-based Maintenance and Evolution with GenAI: A Look into the Future},
    author={Luciano Marchezan, Wesley K. G. Assunc{c}~ao, Edvin Herac and
  Alexander Egyed},
    journal={arXiv preprint arXiv:2407.07269},
    year={2024},
    archivePrefix={arXiv},
    eprint={2407.07269},
    primaryClass={cs.SE}
}