Despite progress in providing software engineers with tools that automate an increasing number of development tasks, complex activities like redesigning and reengineering existing software remain resource intensive or are supported by tools that are error prone. Complex, but common tasks in industry, like evolving large codebases (1M+ SLOC) to meet changing needs, still rely on costly manual efforts and incur significant technical risk. In one example, an organization that we work with estimated 14,000 hours of development work alone (excluding integration and testing) to isolate a feature from the underlying hardware platform. These examples are pervasive in industry. Software engineering research has taken providing effective tools for software evolution for granted for far too long. The time is right for research to take advantage of advances in search-based software engineering and create the next generation of industry-relevant automated software evolution tools. This paper lays out a vision for automated refactoring at scale towards this goal.

@inproceedings{paperbot5748,
  title = {Next generation automated software evolution refactoring at scale},
  author = {James Ivers and Ipek Ozkaya and Robert L. Nord and Chris Seifried},
  booktitle = {FSE},
  year = {2020},
  doi = {10.1145/3368089.3417042}
}