This project investigates the feasibility of using communicative AI (Large Language Models) to extend the capabilities of parser-based software rejuvenation methodologies. The goal is to reduce the required skills, competencies, efforts, and other perceived hurdles when applying such methodologies in industry.
Software maintenance is estimated at 75% to 90% of software development lifecycle cost, and its cost is predicted to grow. As systems stretch beyond their limits, maintaining and refactoring code requires ever-increasing effort and introduces serious risks since crucial business assets are often hidden in legacy components.
The feasibility and added value of the new approach are validated through use case studies using real-life applications from the medical domain in collaboration with Philips IGT.