Abstract
This paper tells the story of the development of RacerD, a static program analysis for detecting data races that is in production at Facebook. The technical details of RacerD are described in a separate paper; we concentrate here on how the project unfolded from a human point of view. The paper describes, in this specific case, the benefits of feedback between science and engineering, the tension encountered between principle and compromise, and how being flexible and adaptable in the presence of a changing engineering context can lead to surprising results which far exceed initial expectations. I hope to give the reader an impression of what it is like to develop advanced static analyses in industry, how it is both different from and similar to developing analyses for the purpose of advancing science.
