George Candea | EPFL Graph Search

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Automated Verification of Network Function Binaries

George Candea, Solal Vincenzo Pirelli

Formally verifying the correctness of software network functions (NFs) is necessary for network reliability, yet existing techniques require full source code and mandate the use of specific data structures. We describe an automated technique to verify NF binaries, making verification usable by network operators even on proprietary code. To solve the key challenge of bridging the abstraction levels of NF implementations and specifications without special-casing a set of data structures, we observe that data structures used by NFs can be modeled as maps, and introduce a universal type to specify both NFs and their data structures, the "ghost map". In addition, we observe that the interactions between an NF and its environment are sufficient to infer control flow and types, removing the requirement for source code. We implement our technique in Klint, a tool with which we verify, in minutes, that 7 NF binaries satisfy their specifications, without limiting developers' choices of data structures. The specifications are written in Python and use maps to model state. Klint can also verify an entire NF binary stack, all the way down to the NIC driver, using a minimal operating system. Operators can thus verify NF binaries, without source code or debug symbols, without requiring developers to use specific programming languages or data structures, and without trusting any software except Klint.

USENIX Association2022

Performance Interfaces for Network Functions

George Candea, Rishabh Ramesh Iyer

Modern programmers routinely use third-party code, and infrastructure operators deploy software they did not write. This would not be possible without semantic interfaces---documentation, header files, specifications---that succinctly describe what that third-party code does. We propose performance interfaces as a way to describe a system's performance, akin to how a semantic interface describes its functionality. We concretize this idea in the domain of network functions (NFs) and present a tool (PIX) that automatically extracts performance interfaces from NF implementations. We evaluate PIX on 12 NFs, including several used in production. The resulting performance interfaces are accurate yet orders of magnitude simpler than the code itself and take minutes to extract. We show how developers and operators can use performance interfaces to identify performance regressions, diagnose and fix performance bugs and identify the latency impact of NIC offloads.

USENIX Association2022

A Simpler and Faster NIC Driver Model for Network Functions

George Candea, Solal Vincenzo Pirelli

The advent of software network functions calls for stronger correctness guarantees and higher performance at every level of the stack. Current network stacks trade simplicity for performance and flexibility, especially in their driver model. We show that performance and simplicity can coexist, at the cost of some flexibility, with a new NIC driver model tailored to network functions. The key idea behind our model is that the driver can efficiently reuse packet buffers because buffers follow a single logical path. We implement a driver for the Intel 82599 network card in 550 lines of code. By merely replacing the state-of-theart driver with our driver, formal verification of the entire software stack completes in 7x less time, while the verified functions’ throughput improves by 160%. Our driver also beats, on realistic workloads, the throughput of drivers that cannot yet be formally verified, thanks to its low variability and resource use. Our code is available at github.com/dslab-epfl/tinynf.

2021