21,865 research outputs found
Automatic Verification of Message-Based Device Drivers
We develop a practical solution to the problem of automatic verification of
the interface between device drivers and the OS. Our solution relies on a
combination of improved driver architecture and verification tools. It supports
drivers written in C and can be implemented in any existing OS, which sets it
apart from previous proposals for verification-friendly drivers. Our
Linux-based evaluation shows that this methodology amplifies the power of
existing verification tools in detecting driver bugs, making it possible to
verify properties beyond the reach of traditional techniques.Comment: In Proceedings SSV 2012, arXiv:1211.587
Automatic Abstraction in SMT-Based Unbounded Software Model Checking
Software model checkers based on under-approximations and SMT solvers are
very successful at verifying safety (i.e. reachability) properties. They
combine two key ideas -- (a) "concreteness": a counterexample in an
under-approximation is a counterexample in the original program as well, and
(b) "generalization": a proof of safety of an under-approximation, produced by
an SMT solver, are generalizable to proofs of safety of the original program.
In this paper, we present a combination of "automatic abstraction" with the
under-approximation-driven framework. We explore two iterative approaches for
obtaining and refining abstractions -- "proof based" and "counterexample based"
-- and show how they can be combined into a unified algorithm. To the best of
our knowledge, this is the first application of Proof-Based Abstraction,
primarily used to verify hardware, to Software Verification. We have
implemented a prototype of the framework using Z3, and evaluate it on many
benchmarks from the Software Verification Competition. We show experimentally
that our combination is quite effective on hard instances.Comment: Extended version of a paper in the proceedings of CAV 201
Generalized Strong Preservation by Abstract Interpretation
Standard abstract model checking relies on abstract Kripke structures which
approximate concrete models by gluing together indistinguishable states, namely
by a partition of the concrete state space. Strong preservation for a
specification language L encodes the equivalence of concrete and abstract model
checking of formulas in L. We show how abstract interpretation can be used to
design abstract models that are more general than abstract Kripke structures.
Accordingly, strong preservation is generalized to abstract
interpretation-based models and precisely related to the concept of
completeness in abstract interpretation. The problem of minimally refining an
abstract model in order to make it strongly preserving for some language L can
be formulated as a minimal domain refinement in abstract interpretation in
order to get completeness w.r.t. the logical/temporal operators of L. It turns
out that this refined strongly preserving abstract model always exists and can
be characterized as a greatest fixed point. As a consequence, some well-known
behavioural equivalences, like bisimulation, simulation and stuttering, and
their corresponding partition refinement algorithms can be elegantly
characterized in abstract interpretation as completeness properties and
refinements
Generalizing the Paige-Tarjan Algorithm by Abstract Interpretation
The Paige and Tarjan algorithm (PT) for computing the coarsest refinement of
a state partition which is a bisimulation on some Kripke structure is well
known. It is also well known in model checking that bisimulation is equivalent
to strong preservation of CTL, or, equivalently, of Hennessy-Milner logic.
Drawing on these observations, we analyze the basic steps of the PT algorithm
from an abstract interpretation perspective, which allows us to reason on
strong preservation in the context of generic inductively defined (temporal)
languages and of possibly non-partitioning abstract models specified by
abstract interpretation. This leads us to design a generalized Paige-Tarjan
algorithm, called GPT, for computing the minimal refinement of an abstract
interpretation-based model that strongly preserves some given language. It
turns out that PT is a straight instance of GPT on the domain of state
partitions for the case of strong preservation of Hennessy-Milner logic. We
provide a number of examples showing that GPT is of general use. We first show
how a well-known efficient algorithm for computing stuttering equivalence can
be viewed as a simple instance of GPT. We then instantiate GPT in order to
design a new efficient algorithm for computing simulation equivalence that is
competitive with the best available algorithms. Finally, we show how GPT allows
to compute new strongly preserving abstract models by providing an efficient
algorithm that computes the coarsest refinement of a given partition that
strongly preserves the language generated by the reachability operator.Comment: Keywords: Abstract interpretation, abstract model checking, strong
preservation, Paige-Tarjan algorithm, refinement algorith
Instruction-Level Abstraction (ILA): A Uniform Specification for System-on-Chip (SoC) Verification
Modern Systems-on-Chip (SoC) designs are increasingly heterogeneous and
contain specialized semi-programmable accelerators in addition to programmable
processors. In contrast to the pre-accelerator era, when the ISA played an
important role in verification by enabling a clean separation of concerns
between software and hardware, verification of these "accelerator-rich" SoCs
presents new challenges. From the perspective of hardware designers, there is a
lack of a common framework for the formal functional specification of
accelerator behavior. From the perspective of software developers, there exists
no unified framework for reasoning about software/hardware interactions of
programs that interact with accelerators. This paper addresses these challenges
by providing a formal specification and high-level abstraction for accelerator
functional behavior. It formalizes the concept of an Instruction Level
Abstraction (ILA), developed informally in our previous work, and shows its
application in modeling and verification of accelerators. This formal ILA
extends the familiar notion of instructions to accelerators and provides a
uniform, modular, and hierarchical abstraction for modeling software-visible
behavior of both accelerators and programmable processors. We demonstrate the
applicability of the ILA through several case studies of accelerators (for
image processing, machine learning, and cryptography), and a general-purpose
processor (RISC-V). We show how the ILA model facilitates equivalence checking
between two ILAs, and between an ILA and its hardware finite-state machine
(FSM) implementation. Further, this equivalence checking supports accelerator
upgrades using the notion of ILA compatibility, similar to processor upgrades
using ISA compatibility.Comment: 24 pages, 3 figures, 3 table
Integrated Design Tools for Embedded Control Systems
Currently, computer-based control systems are still being implemented using the same techniques as 10 years ago. The purpose of this project is the development of a design framework, consisting of tools and libraries, which allows the designer to build high reliable heterogeneous real-time embedded systems in a very short time at a fraction of the present day costs. The ultimate focus of current research is on transformation control laws to efficient concurrent algorithms, with concerns about important non-functional real-time control systems demands, such as fault-tolerance, safety,\ud
reliability, etc.\ud
The approach is based on software implementation of CSP process algebra, in a modern way (pure objectoriented design in Java). Furthermore, it is intended that the tool will support the desirable system-engineering stepwise refinement design approach, relying on past research achievements ¿ the mechatronics design trajectory based on the building-blocks approach, covering all complex (mechatronics) engineering phases: physical system modeling, control law design, embedded control system implementation and real-life realization. Therefore, we expect that this project will result in an\ud
adequate tool, with results applicable in a wide range of target hardware platforms, based on common (off-theshelf) distributed heterogeneous (cheap) processing units
MeGARA: Menu-based Game Abstraction and Abstraction Refinement of Markov Automata
Markov automata combine continuous time, probabilistic transitions, and
nondeterminism in a single model. They represent an important and powerful way
to model a wide range of complex real-life systems. However, such models tend
to be large and difficult to handle, making abstraction and abstraction
refinement necessary. In this paper we present an abstraction and abstraction
refinement technique for Markov automata, based on the game-based and
menu-based abstraction of probabilistic automata. First experiments show that a
significant reduction in size is possible using abstraction.Comment: In Proceedings QAPL 2014, arXiv:1406.156
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