Challenge: Distributed systems are notoriously hard to get right. Programming these systems is challenging because of the need to reason about correctness in the presence of myriad possible interleaving of messages and failures. Unsurprisingly, it is common for service teams to uncover correctness bugs after deployment. Formal methods can play an important role in addressing this challenge!
P Overview: P is a state machine based programming language for formally modeling and specifying complex distributed systems. P allows programmers to model their system design as a collection of communicating state machines. P supports several backend analysis engines (based on automated reasoning techniques like model checking and symbolic execution) to check that the distributed system modeled in P satisfy the desired correctness specifications.
If you are wondering "why do formal methods at all?" or "how is AWS using P to gain confidence in correctness of their services?", the following re:Invent 2023 talk answers this question, provides an overview of P, and its impact inside AWS: (Re:Invent 2023 Talk) Gain confidence in system correctness & resilience with Formal Methods (Finding Critical Bugs Early!!)
Impact: P is currently being used extensively inside Amazon (AWS) for analysis of complex distributed systems. For example, Amazon S3 used P to formally reason about the core distributed protocols involved in its strong consistency launch. Teams across AWS are now using P for thinking and reasoning about their systems formally. P is also being used for programming safe robotics systems in Academia. P was first used to implement and validate the USB device driver stack that ships with Microsoft Windows 8 and Windows Phone.
Experience and lessons learned: In our experience of using P inside AWS, Academia, and Microsoft. We have observed that P has helped developers in three critical ways: (1) P as a thinking tool: Writing formal specifications in P forces developers to think about their system design rigorously, and in turn helped in bridging gaps in their understanding of the system. A large fraction of the bugs can be eliminated in the process of writing specifications itself! (2) P as a bug finder: Model checking helped find corner case bugs in system design that were missed by stress and integration testing. (3) P helped boost developer velocity: After the initial overhead of creating the formal models, future updates and feature additions could be rolled out faster as these non-trivial changes are rigorously validated before implementation.
✨ Programming concurrent, distributed systems is fun but challenging, however, a pinch of programming language design with a dash of automated reasoning can go a long way in addressing the challenge and amplify the fun!. ✨
You can find most of the information about the P framework on: https://p-org.github.io/P/.
What is P?, Getting Started, Tutorials, Case Studies and related Research Publications. If you have any further questions, please feel free to create an issue, ask on discussions, or email us
P has always been a collaborative project between industry and academia (since 2013) 🥁. The P team welcomes contributions and suggestions from all of you!! 👊. See CONTRIBUTING for more information.