4,825 research outputs found
Syntactic Abstraction of B Models to Generate Tests
In a model-based testing approach as well as for the verification of
properties, B models provide an interesting solution. However, for industrial
applications, the size of their state space often makes them hard to handle. To
reduce the amount of states, an abstraction function can be used, often
combining state variable elimination and domain abstractions of the remaining
variables. This paper complements previous results, based on domain abstraction
for test generation, by adding a preliminary syntactic abstraction phase, based
on variable elimination. We define a syntactic transformation that suppresses
some variables from a B event model, in addition to a method that chooses
relevant variables according to a test purpose. We propose two methods to
compute an abstraction A of an initial model M. The first one computes A as a
simulation of M, and the second one computes A as a bisimulation of M. The
abstraction process produces a finite state system. We apply this abstraction
computation to a Model Based Testing process.Comment: Tests and Proofs 2010, Malaga : Spain (2010
Enhancing Predicate Pairing with Abstraction for Relational Verification
Relational verification is a technique that aims at proving properties that
relate two different program fragments, or two different program runs. It has
been shown that constrained Horn clauses (CHCs) can effectively be used for
relational verification by applying a CHC transformation, called predicate
pairing, which allows the CHC solver to infer relations among arguments of
different predicates. In this paper we study how the effects of the predicate
pairing transformation can be enhanced by using various abstract domains based
on linear arithmetic (i.e., the domain of convex polyhedra and some of its
subdomains) during the transformation. After presenting an algorithm for
predicate pairing with abstraction, we report on the experiments we have
performed on over a hundred relational verification problems by using various
abstract domains. The experiments have been performed by using the VeriMAP
transformation and verification system, together with the Parma Polyhedra
Library (PPL) and the Z3 solver for CHCs.Comment: Pre-proceedings paper presented at the 27th International Symposium
on Logic-Based Program Synthesis and Transformation (LOPSTR 2017), Namur,
Belgium, 10-12 October 2017 (arXiv:1708.07854
Probabilistic Program Abstractions
Abstraction is a fundamental tool for reasoning about complex systems.
Program abstraction has been utilized to great effect for analyzing
deterministic programs. At the heart of program abstraction is the relationship
between a concrete program, which is difficult to analyze, and an abstract
program, which is more tractable. Program abstractions, however, are typically
not probabilistic. We generalize non-deterministic program abstractions to
probabilistic program abstractions by explicitly quantifying the
non-deterministic choices. Our framework upgrades key definitions and
properties of abstractions to the probabilistic context. We also discuss
preliminary ideas for performing inference on probabilistic abstractions and
general probabilistic programs
Predicate Abstraction with Indexed Predicates
Predicate abstraction provides a powerful tool for verifying properties of
infinite-state systems using a combination of a decision procedure for a subset
of first-order logic and symbolic methods originally developed for finite-state
model checking. We consider models containing first-order state variables,
where the system state includes mutable functions and predicates. Such a model
can describe systems containing arbitrarily large memories, buffers, and arrays
of identical processes. We describe a form of predicate abstraction that
constructs a formula over a set of universally quantified variables to describe
invariant properties of the first-order state variables. We provide a formal
justification of the soundness of our approach and describe how it has been
used to verify several hardware and software designs, including a
directory-based cache coherence protocol.Comment: 27 pages, 4 figures, 1 table, short version appeared in International
Conference on Verification, Model Checking and Abstract Interpretation
(VMCAI'04), LNCS 2937, pages = 267--28
State space c-reductions for concurrent systems in rewriting logic
We present c-reductions, a state space reduction technique.
The rough idea is to exploit some equivalence relation on states (possibly capturing system regularities) that preserves behavioral properties, and explore the induced quotient system. This is done by means of a canonizer
function, which maps each state into a (non necessarily unique) canonical representative of its equivalence class. The approach exploits the expressiveness of rewriting logic and its realization in Maude to enjoy several advantages over similar approaches: exibility and simplicity in
the definition of the reductions (supporting not only traditional symmetry reductions, but also name reuse and name abstraction); reasoning support for checking and proving correctness of the reductions; and automatization
of the reduction infrastructure via Maude's meta-programming
features. The approach has been validated over a set of representative case studies, exhibiting comparable results with respect to other tools
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