Are you an EPFL student looking for a semester project?
Work with us on data science and visualisation projects, and deploy your project as an app on top of Graph Search.
Publication
Are you an EPFL student looking for a semester project?
Work with us on data science and visualisation projects, and deploy your project as an app on top of Graph Search.
Software network functions (NFs), such as a network address translator, load balancer, or proxy, promise to bring flexibility and rapid innovation to computer networks and to reduce operational costs. However, continuous updates and flexibility typically come with the risk of bugs. As networks are a critical component of modern computing (e.g., the Internet), both users and operators demand that they be as reliable as economically possible.
One way to guarantee reliability is by formal verification. To prove the absence of bugs, formal verification applies rigorous mathematical logic.
State-of-the-art formal verification methods either require substantial effort and verification expertise on the part of the practitioner or lack completeness. In particular, theorem proving, to guide a mechanical proof checker, requires a human to annotate the code they verify with logical steps, and this annotation is something for which NF developers typically lack the time or expertise to do. Whereas, symbolic execution (SE) can analyze the code automatically, hence requiring significantly less effort; but it has difficulties with the so-called path explosion.
Fortunately, software NFs have a special structure:
In this dissertation, we present Vigor, a new method and tool for verifying software NFs; it exploits this special structure of NFs. We make two contributions:
First, we show that it is possible to develop software NFs that are guaranteed to satisfy a formal specification and at the same time exhibit competitive performance. We develop a practical toolchain for developing NFs in C by using a standard fast packet-processing framework. Vigor provides a library of formally verified data structures (libVig); this library replaces the parts posing a challenge to SE. The Vigor toolchain applies exhaustive SE to the NF code that uses libVig. Vigor introduces a new technique, which we call "lazy proofs", for automatically stitching the proofs together and, ultimately, for certifying the whole NF correct relative to its functional specification.
Second, we show that practical high-level semantic verification of software NFs is possible. By practical, we mean a verification that (a) requires no verification input other than the specification (push-button), (b) guarantees correctness of the entire runtime software stack, i.e., OS, driver, framework, and NF (full-stack), and (c) does not require writing a comprehensive specification to verify the first line of code (pay-as-you-go).
In summary, Vigor provides push-button, full-stack, pay-as-you-go formal verification of software NFs with no reduction in NF performance or developer productivity.
To substantiate our claims we implement five NFs, prove their correctness, and show that their performance is as good as the performance of the fastest non-verified software NFs. All of our NFs achieve a median latency of 4.1±0.2 us and over 4 Mpps throughput with 10 Gbps network interfaces. In terms of developer productivity, an average partial property takes 6.4 lines of Python specification, and the verification of the full stack (NF, packet-processing framework, OS, driver) takes up to one day. The Vigor toolchain is open-source and is available, along with tutorials and example NF implementations, at vigor.epfl.ch.
Viktor Kuncak, Mario Bucev, Dragana Milovancevic, Samuel Chassot
,