37,576 research outputs found
Memory Efficient Algorithms for the Verification of Temporal Properties
peer reviewedaudience: researcherThis paper addresses the problem of designing memory-efficient algorithms for the verification of temporal properties of finite-state programs. Both the programs and their desired temporal properties are modeled as automata on infinite words (BĂĽchi automata). Verification is then reduced to checking the emptiness of the automaton resulting from the product of the program and the property. This problem is usually solved by computing the strongly connected components of the graph representing the product automaton. Here, we present algorithms which solve the emptiness problem without explicitly constructing the strongly connected components of the product graph. By allowing the algorithms to err with some probability, we can implement them with a randomly accessed memory of size O(n) bits, where n is the number of states of the graph, instead of O(n log n) bits that the presently known algorithms require
Platform Dependent Verification: On Engineering Verification Tools for 21st Century
The paper overviews recent developments in platform-dependent explicit-state
LTL model checking.Comment: In Proceedings PDMC 2011, arXiv:1111.006
Distributed Verification of Rare Properties using Importance Splitting Observers
Rare properties remain a challenge for statistical model checking (SMC) due
to the quadratic scaling of variance with rarity. We address this with a
variance reduction framework based on lightweight importance splitting
observers. These expose the model-property automaton to allow the construction
of score functions for high performance algorithms.
The confidence intervals defined for importance splitting make it appealing
for SMC, but optimising its performance in the standard way makes distribution
inefficient. We show how it is possible to achieve equivalently good results in
less time by distributing simpler algorithms. We first explore the challenges
posed by importance splitting and present an algorithm optimised for
distribution. We then define a specific bounded time logic that is compiled
into memory-efficient observers to monitor executions. Finally, we demonstrate
our framework on a number of challenging case studies
Efficient Symmetry Reduction and the Use of State Symmetries for Symbolic Model Checking
One technique to reduce the state-space explosion problem in temporal logic
model checking is symmetry reduction. The combination of symmetry reduction and
symbolic model checking by using BDDs suffered a long time from the
prohibitively large BDD for the orbit relation. Dynamic symmetry reduction
calculates representatives of equivalence classes of states dynamically and
thus avoids the construction of the orbit relation. In this paper, we present a
new efficient model checking algorithm based on dynamic symmetry reduction. Our
experiments show that the algorithm is very fast and allows the verification of
larger systems. We additionally implemented the use of state symmetries for
symbolic symmetry reduction. To our knowledge we are the first who investigated
state symmetries in combination with BDD based symbolic model checking
Quantitative Regular Expressions for Arrhythmia Detection Algorithms
Motivated by the problem of verifying the correctness of arrhythmia-detection
algorithms, we present a formalization of these algorithms in the language of
Quantitative Regular Expressions. QREs are a flexible formal language for
specifying complex numerical queries over data streams, with provable runtime
and memory consumption guarantees. The medical-device algorithms of interest
include peak detection (where a peak in a cardiac signal indicates a heartbeat)
and various discriminators, each of which uses a feature of the cardiac signal
to distinguish fatal from non-fatal arrhythmias. Expressing these algorithms'
desired output in current temporal logics, and implementing them via monitor
synthesis, is cumbersome, error-prone, computationally expensive, and sometimes
infeasible.
In contrast, we show that a range of peak detectors (in both the time and
wavelet domains) and various discriminators at the heart of today's
arrhythmia-detection devices are easily expressible in QREs. The fact that one
formalism (QREs) is used to describe the desired end-to-end operation of an
arrhythmia detector opens the way to formal analysis and rigorous testing of
these detectors' correctness and performance. Such analysis could alleviate the
regulatory burden on device developers when modifying their algorithms. The
performance of the peak-detection QREs is demonstrated by running them on real
patient data, on which they yield results on par with those provided by a
cardiologist.Comment: CMSB 2017: 15th Conference on Computational Methods for Systems
Biolog
Efficient Large-scale Trace Checking Using MapReduce
The problem of checking a logged event trace against a temporal logic
specification arises in many practical cases. Unfortunately, known algorithms
for an expressive logic like MTL (Metric Temporal Logic) do not scale with
respect to two crucial dimensions: the length of the trace and the size of the
time interval for which logged events must be buffered to check satisfaction of
the specification. The former issue can be addressed by distributed and
parallel trace checking algorithms that can take advantage of modern cloud
computing and programming frameworks like MapReduce. Still, the latter issue
remains open with current state-of-the-art approaches.
In this paper we address this memory scalability issue by proposing a new
semantics for MTL, called lazy semantics. This semantics can evaluate temporal
formulae and boolean combinations of temporal-only formulae at any arbitrary
time instant. We prove that lazy semantics is more expressive than standard
point-based semantics and that it can be used as a basis for a correct
parametric decomposition of any MTL formula into an equivalent one with
smaller, bounded time intervals. We use lazy semantics to extend our previous
distributed trace checking algorithm for MTL. We evaluate the proposed
algorithm in terms of memory scalability and time/memory tradeoffs.Comment: 13 pages, 8 figure
Symmetry Reduction Enables Model Checking of More Complex Emergent Behaviours of Swarm Navigation Algorithms
The emergent global behaviours of robotic swarms are important to achieve
their navigation task goals. These emergent behaviours can be verified to
assess their correctness, through techniques like model checking. Model
checking exhaustively explores all possible behaviours, based on a discrete
model of the system, such as a swarm in a grid. A common problem in model
checking is the state-space explosion that arises when the states of the model
are numerous. We propose a novel implementation of symmetry reduction, in the
form of encoding navigation algorithms relatively with respect to a reference,
based on the symmetrical properties of swarms in grids. We applied the relative
encoding to a swarm navigation algorithm, Alpha, modelled for the NuSMV model
checker. A comparison of the state-space and verification results with an
absolute (or global) and a relative encoding of the Alpha algorithm highlights
the advantages of our approach, allowing model checking larger grid sizes and
number of robots, and consequently, verifying more complex emergent behaviours.
For example, a property was verified for a grid with 3 robots and a maximum
allowed size of 8x8 cells in a global encoding, whereas this size was increased
to 16x16 using a relative encoding. Also, the time to verify a property for a
swarm of 3 robots in a 6x6 grid was reduced from almost 10 hours to only 7
minutes. Our approach is transferable to other swarm navigation algorithms.Comment: Accepted for presentation in Towards Autonomous Robotic Systems
(TAROS) 2015, Liverpool, U
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