Ph.D. Program in Software Engineering, Institute for Software Research
Carnegie Mellon University
A Turing Test for Genetic Improvement
Genetic improvement (GI) is a research field that aims to develop search-based techniques for improving existing code. GI has been used to automatically repair bugs, reduce energy consumption, and to improve run-time performance. In this talk, I will reflect on the often-overlooked relationship between GI and developers within the context of continually evolving software systems. I will introduce a distinction between transparent and opaque patches based on their intended lifespan and developer interaction. Finally, I will outline a Turing test for assessing the ability of a GI system to produce opaque patches that are acceptable to humans.