19,202 research outputs found
Verifiably-safe software-defined networks for CPS
Next generation cyber-physical systems (CPS) are expected to be deployed in domains which require scalability as well as performance under dynamic conditions. This scale and dynamicity will require that CPS communication networks be programmatic (i.e., not requiring manual intervention at any stage), but still maintain iron-clad safety guarantees. Software-defined networking standards like OpenFlow provide a means for scalably building tailor-made network architectures, but there is no guarantee that these systems are safe, correct, or secure. In this work we propose a methodology and accompanying tools for specifying and modeling distributed systems such that existing formal verification techniques can be transparently used to analyze critical requirements and properties prior to system implementation. We demonstrate this methodology by iteratively modeling and verifying an OpenFlow learning switch network with respect to network correctness, network convergence, and mobility-related properties. We posit that a design strategy based on the complementary pairing of software-defined networking and formal verification would enable the CPS community to build next-generation systems without sacrificing the safety and reliability that these systems must deliver
Applying Formal Methods to Networking: Theory, Techniques and Applications
Despite its great importance, modern network infrastructure is remarkable for
the lack of rigor in its engineering. The Internet which began as a research
experiment was never designed to handle the users and applications it hosts
today. The lack of formalization of the Internet architecture meant limited
abstractions and modularity, especially for the control and management planes,
thus requiring for every new need a new protocol built from scratch. This led
to an unwieldy ossified Internet architecture resistant to any attempts at
formal verification, and an Internet culture where expediency and pragmatism
are favored over formal correctness. Fortunately, recent work in the space of
clean slate Internet design---especially, the software defined networking (SDN)
paradigm---offers the Internet community another chance to develop the right
kind of architecture and abstractions. This has also led to a great resurgence
in interest of applying formal methods to specification, verification, and
synthesis of networking protocols and applications. In this paper, we present a
self-contained tutorial of the formidable amount of work that has been done in
formal methods, and present a survey of its applications to networking.Comment: 30 pages, submitted to IEEE Communications Surveys and Tutorial
Verifying the Safety of a Flight-Critical System
This paper describes our work on demonstrating verification technologies on a
flight-critical system of realistic functionality, size, and complexity. Our
work targeted a commercial aircraft control system named Transport Class Model
(TCM), and involved several stages: formalizing and disambiguating requirements
in collaboration with do- main experts; processing models for their use by
formal verification tools; applying compositional techniques at the
architectural and component level to scale verification. Performed in the
context of a major NASA milestone, this study of formal verification in
practice is one of the most challenging that our group has performed, and it
took several person months to complete it. This paper describes the methodology
that we followed and the lessons that we learned.Comment: 17 pages, 5 figure
Model checking learning agent systems using Promela with embedded C code and abstraction
As autonomous systems become more prevalent, methods for their verification will become more
widely used. Model checking is a formal verification technique that can help ensure the safety of autonomous
systems, but in most cases it cannot be applied by novices, or in its straight \off-the-shelf" form. In order
to be more widely applicable it is crucial that more sophisticated techniques are used, and are presented
in a way that is reproducible by engineers and verifiers alike. In this paper we demonstrate in detail two
techniques that are used to increase the power of model checking using the model checker SPIN. The first
of these is the use of embedded C code within Promela specifications, in order to accurately re
ect robot
movement. The second is to use abstraction together with a simulation relation to allow us to verify multiple
environments simultaneously. We apply these techniques to a fairly simple system in which a robot moves
about a fixed circular environment and learns to avoid obstacles. The learning algorithm is inspired by the
way that insects learn to avoid obstacles in response to pain signals received from their antennae. Crucially,
we prove that our abstraction is sound for our example system { a step that is often omitted but is vital if
formal verification is to be widely accepted as a useful and meaningful approach
Using ACL2 to Verify Loop Pipelining in Behavioral Synthesis
Behavioral synthesis involves compiling an Electronic System-Level (ESL)
design into its Register-Transfer Level (RTL) implementation. Loop pipelining
is one of the most critical and complex transformations employed in behavioral
synthesis. Certifying the loop pipelining algorithm is challenging because
there is a huge semantic gap between the input sequential design and the output
pipelined implementation making it infeasible to verify their equivalence with
automated sequential equivalence checking techniques. We discuss our ongoing
effort using ACL2 to certify loop pipelining transformation. The completion of
the proof is work in progress. However, some of the insights developed so far
may already be of value to the ACL2 community. In particular, we discuss the
key invariant we formalized, which is very different from that used in most
pipeline proofs. We discuss the needs for this invariant, its formalization in
ACL2, and our envisioned proof using the invariant. We also discuss some
trade-offs, challenges, and insights developed in course of the project.Comment: In Proceedings ACL2 2014, arXiv:1406.123
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