FAUSTA: Scaling Dynamic Analysis with Traffic Generation at WhatsApp

IEEE International Conference on Software Testing, Verification and Validation (ICST)

Abstract

We introduce FAUSTA, an algorithmic traffic generation platform that enables analysis and testing at scale. FAUSTA has been deployed at Meta to analyze and test the WhatsApp platform infrastructure since September 2020, enabling WhatsApp developers to deploy reliable code changes to a code base of millions of lines of code, supporting over 2 billion users who rely on WhatsApp for their daily communications. FAUSTA covers expected and unexpected program behaviors in a privacy-safe controlled environment to support multiple use cases such as reliability testing, privacy analysis and performance regression detection. It currently supports three different algorithmic input generation strategies, each of which construct realistic backend server traffic that closely simulates production data, without replaying any real user data. FAUSTA has been deployed and closely integrated into the WhatsApp continuous integration process, catching bugs in development before they hit production. We report on the development and deployment of FAUSTA’s reliability use case between September 2020 and August 2021. During this period it has found 1,876 unique reliability issues, with a fix rate of 74%, indicating a high degree of true positive fault revelation. We also report on the distribution of fault types revealed by FAUSTA, and the correlation between coverage and faults found. Overall, we do find evidence that higher coverage is correlated with fault revelation.

Best Industry Paper Award at ICST 2022

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