2,688 research outputs found
The Parma Polyhedra Library: Toward a Complete Set of Numerical Abstractions for the Analysis and Verification of Hardware and Software Systems
Since its inception as a student project in 2001, initially just for the
handling (as the name implies) of convex polyhedra, the Parma Polyhedra Library
has been continuously improved and extended by joining scrupulous research on
the theoretical foundations of (possibly non-convex) numerical abstractions to
a total adherence to the best available practices in software development. Even
though it is still not fully mature and functionally complete, the Parma
Polyhedra Library already offers a combination of functionality, reliability,
usability and performance that is not matched by similar, freely available
libraries. In this paper, we present the main features of the current version
of the library, emphasizing those that distinguish it from other similar
libraries and those that are important for applications in the field of
analysis and verification of hardware and software systems.Comment: 38 pages, 2 figures, 3 listings, 3 table
Experiments with a Convex Polyhedral Analysis Tool for Logic Programs
Convex polyhedral abstractions of logic programs have been found very useful
in deriving numeric relationships between program arguments in order to prove
program properties and in other areas such as termination and complexity
analysis. We present a tool for constructing polyhedral analyses of
(constraint) logic programs. The aim of the tool is to make available, with a
convenient interface, state-of-the-art techniques for polyhedral analysis such
as delayed widening, narrowing, "widening up-to", and enhanced automatic
selection of widening points. The tool is accessible on the web, permits user
programs to be uploaded and analysed, and is integrated with related program
transformations such as size abstractions and query-answer transformation. We
then report some experiments using the tool, showing how it can be conveniently
used to analyse transition systems arising from models of embedded systems, and
an emulator for a PIC microcontroller which is used for example in wearable
computing systems. We discuss issues including scalability, tradeoffs of
precision and computation time, and other program transformations that can
enhance the results of analysis.Comment: Paper presented at the 17th Workshop on Logic-based Methods in
Programming Environments (WLPE2007
Constraint-based reachability
Iterative imperative programs can be considered as infinite-state systems
computing over possibly unbounded domains. Studying reachability in these
systems is challenging as it requires to deal with an infinite number of states
with standard backward or forward exploration strategies. An approach that we
call Constraint-based reachability, is proposed to address reachability
problems by exploring program states using a constraint model of the whole
program. The keypoint of the approach is to interpret imperative constructions
such as conditionals, loops, array and memory manipulations with the
fundamental notion of constraint over a computational domain. By combining
constraint filtering and abstraction techniques, Constraint-based reachability
is able to solve reachability problems which are usually outside the scope of
backward or forward exploration strategies. This paper proposes an
interpretation of classical filtering consistencies used in Constraint
Programming as abstract domain computations, and shows how this approach can be
used to produce a constraint solver that efficiently generates solutions for
reachability problems that are unsolvable by other approaches.Comment: In Proceedings Infinity 2012, arXiv:1302.310
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Specialising finite domain programs with polyhedra
A procedure is described for tightening domain constraints of finite domain logic programs by applying a static analysis based on convex polyhedra. Individual finite domain constraints are over-approximated by polyhedra to describe the solution space over ninteger variables as an n dimensional polyhedron. This polyhedron is then approximated, using projection, as an n dimensional bounding box that can be used to specialise and improve the domain constraints. The analysis can be implemented straightforwardly and an empirical evaluation of the specialisation technique is given
Stratified Static Analysis Based on Variable Dependencies
In static analysis by abstract interpretation, one often uses widening
operators in order to enforce convergence within finite time to an inductive
invariant. Certain widening operators, including the classical one over finite
polyhedra, exhibit an unintuitive behavior: analyzing the program over a subset
of its variables may lead a more precise result than analyzing the original
program! In this article, we present simple workarounds for such behavior
Generating Property-Directed Potential Invariants By Backward Analysis
This paper addresses the issue of lemma generation in a k-induction-based
formal analysis of transition systems, in the linear real/integer arithmetic
fragment. A backward analysis, powered by quantifier elimination, is used to
output preimages of the negation of the proof objective, viewed as unauthorized
states, or gray states. Two heuristics are proposed to take advantage of this
source of information. First, a thorough exploration of the possible
partitionings of the gray state space discovers new relations between state
variables, representing potential invariants. Second, an inexact exploration
regroups and over-approximates disjoint areas of the gray state space, also to
discover new relations between state variables. k-induction is used to isolate
the invariants and check if they strengthen the proof objective. These
heuristics can be used on the first preimage of the backward exploration, and
each time a new one is output, refining the information on the gray states. In
our context of critical avionics embedded systems, we show that our approach is
able to outperform other academic or commercial tools on examples of interest
in our application field. The method is introduced and motivated through two
main examples, one of which was provided by Rockwell Collins, in a
collaborative formal verification framework.Comment: In Proceedings FTSCS 2012, arXiv:1212.657
Now or never: negotiating efficiently with unknown counterparts
We define a new protocol rule, Now or Never (NoN), for bilateral negotiation processes which allows self-motivated competitive agents to efficiently carry out multi-variable negotiations with remote untrusted parties, where privacy is a major concern and agents know nothing about their opponent. By building on the geometric concepts of convexity and convex hull, NoN ensures a continuous progress of the negotiation, thus neutralising malicious or inefficient opponents. In par- ticular, NoN allows an agent to derive in a finite number of steps, and independently of the behaviour of the opponent, that there is no hope to find an agreement. To be able to make such an inference, the interested agent may rely on herself only, still keeping the highest freedom in the choice of her strategy.
We also propose an actual NoN-compliant strategy for an automated agent and evaluate the computational feasibility of the overall approach on instances of practical size
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