Experience Developing and Deploying Concurrency Analysis at Facebook
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.
Thanks first of all to Jingbo Yang and Ben Jaeger for being so giving of their time, experience and insight when working with Sam Blackshear and I. And thanks to Sam for taking the engineering of RacerD to another level. I am fortunate to have participated in this collaboration with Ben, Jingbo and Sam. I’m grateful to Nikos Gorogiannis and Ilya Sergey for joining and contributing greatly to the project. Finally, special thanks to Bryan O’Sullivan for consistently and enthusiastically supporting this work, and encouraging me to proceed and be bold.
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