56,654 research outputs found
A deductive model checking approach for hybrid systems
In this paper we propose a verification method for hybrid systems that is based on a successive elimination of the various system locations involved. Briefly, with each such elimination we compute a weakest precondition (strongest postcondition) on the predecessor (successor) locations such that the property to be proved cannot be violated. This is done by representing a given verification problem as a second-order predicate logic formula which is to be solved (proved valid) with the help of a second-order quantifier elimination method. In contrast to many ``standard'' model checking approaches the method as described in this paper does not perform a forward or backward reachability analysis. Experiments show that this approach is particularly interesting in cases where a standard reachability analysis would require to travel often through some of the given system locations. In addition, the approach offers possibilities to proceed where ``standard'' reachability analysis approaches do not terminate
COST Action IC 1402 ArVI: Runtime Verification Beyond Monitoring -- Activity Report of Working Group 1
This report presents the activities of the first working group of the COST
Action ArVI, Runtime Verification beyond Monitoring. The report aims to provide
an overview of some of the major core aspects involved in Runtime Verification.
Runtime Verification is the field of research dedicated to the analysis of
system executions. It is often seen as a discipline that studies how a system
run satisfies or violates correctness properties. The report exposes a taxonomy
of Runtime Verification (RV) presenting the terminology involved with the main
concepts of the field. The report also develops the concept of instrumentation,
the various ways to instrument systems, and the fundamental role of
instrumentation in designing an RV framework. We also discuss how RV interplays
with other verification techniques such as model-checking, deductive
verification, model learning, testing, and runtime assertion checking. Finally,
we propose challenges in monitoring quantitative and statistical data beyond
detecting property violation
Induction and Deduction in Baysian Data Analysis
The classical or frequentist approach to statistics (in which inference is centered on significance testing), is associated with a philosophy in which science is deductive and follows Popperis doctrine of falsification. In contrast, Bayesian inference is commonly associated with inductive reasoning and the idea that a model can be dethroned by a competing model but can never be directly falsified by a significance test. The purpose of this article is to break these associations, which I think are incorrect and have been detrimental to statistical practice, in that they have steered falsificationists away from the very useful tools of Bayesian inference and have discouraged Bayesians from checking the fit of their models. From my experience using and developing Bayesian methods in social and environmental science, I have found model checking and falsification to be central in the modeling process.philosophy of statistics, decision theory, subjective probability, Bayesianism, falsification, induction, frequentism
Towards Intelligent Databases
This article is a presentation of the objectives and techniques
of deductive databases. The deductive approach to databases aims at extending
with intensional definitions other database paradigms that describe
applications extensionaUy. We first show how constructive specifications can
be expressed with deduction rules, and how normative conditions can be defined
using integrity constraints. We outline the principles of bottom-up and
top-down query answering procedures and present the techniques used for
integrity checking. We then argue that it is often desirable to manage with
a database system not only database applications, but also specifications of
system components. We present such meta-level specifications and discuss
their advantages over conventional approaches
Sciduction: Combining Induction, Deduction, and Structure for Verification and Synthesis
Even with impressive advances in automated formal methods, certain problems
in system verification and synthesis remain challenging. Examples include the
verification of quantitative properties of software involving constraints on
timing and energy consumption, and the automatic synthesis of systems from
specifications. The major challenges include environment modeling,
incompleteness in specifications, and the complexity of underlying decision
problems.
This position paper proposes sciduction, an approach to tackle these
challenges by integrating inductive inference, deductive reasoning, and
structure hypotheses. Deductive reasoning, which leads from general rules or
concepts to conclusions about specific problem instances, includes techniques
such as logical inference and constraint solving. Inductive inference, which
generalizes from specific instances to yield a concept, includes algorithmic
learning from examples. Structure hypotheses are used to define the class of
artifacts, such as invariants or program fragments, generated during
verification or synthesis. Sciduction constrains inductive and deductive
reasoning using structure hypotheses, and actively combines inductive and
deductive reasoning: for instance, deductive techniques generate examples for
learning, and inductive reasoning is used to guide the deductive engines.
We illustrate this approach with three applications: (i) timing analysis of
software; (ii) synthesis of loop-free programs, and (iii) controller synthesis
for hybrid systems. Some future applications are also discussed
Deductive Verification of Parallel Programs Using Why3
The Message Passing Interface specification (MPI) defines a portable
message-passing API used to program parallel computers. MPI programs manifest a
number of challenges on what concerns correctness: sent and expected values in
communications may not match, resulting in incorrect computations possibly
leading to crashes; and programs may deadlock resulting in wasted resources.
Existing tools are not completely satisfactory: model-checking does not scale
with the number of processes; testing techniques wastes resources and are
highly dependent on the quality of the test set.
As an alternative, we present a prototype for a type-based approach to
programming and verifying MPI like programs against protocols. Protocols are
written in a dependent type language designed so as to capture the most common
primitives in MPI, incorporating, in addition, a form of primitive recursion
and collective choice. Protocols are then translated into Why3, a deductive
software verification tool. Source code, in turn, is written in WhyML, the
language of the Why3 platform, and checked against the protocol. Programs that
pass verification are guaranteed to be communication safe and free from
deadlocks.
We verified several parallel programs from textbooks using our approach, and
report on the outcome.Comment: In Proceedings ICE 2015, arXiv:1508.0459
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