A turing test for genetic improvement
Afsoon Afzal, Jeremy Lacomis, Claire Le Goues, Christopher S. Timperley · 2018
Genetic improvement 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 paper, we reflect on the often-overlooked relationship between GI and developers within the context of continually evolving software systems. We introduce a distinction between transparent and opaque patches based on intended lifespan and developer interaction. Finally, we outline a Turing test for assessing the ability of a GI system to produce opaque patches that are acceptable to humans. This motivates research into the role GI systems will play in transparent development contexts.