Debugging Multithreaded Codebases at Scale

Finding race conditions in concurrent code using just-in-time binary instrumentation, fuzzing, and time travel

Multithreaded application architectures help improve performance; but they also increase the risk of concurrency issues such as deadlocks or race conditions. And these can be non-trivial to reproduce...

This technical paper reveals the technologies and techniques at your disposal for quickly diagnosing the root cause of multithreading issues and finding race conditions before your customers do:

• Time travel debugging - making bugs 100% reproducible, every time
• Thread fuzzing - exposing concurrency issues during testing by interfering with the regular scheduling of C++ threads
• Multiprocess correlation - debugging shared memory corruption more easily

These are already used by engineering teams at leading tech firms like SAP, Bloomberg, Palo Alto Networks, Juniper, Synopsys, Siemens EDA and more.

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