86 research outputs found
An Introduction to Pervasive Interface Automata
Pervasive systems are often context-dependent, component based systems in which components expose interfaces and offer one or more services. These systems may evolve in unpredictable ways, often through component replacement. We present pervasive interface automata as a formalism for modelling components and their composition. Pervasive interface automata are based on the interface automata of Henzinger et al, with several significant differences. We expand their notion of input and output actions to combinations of input, output actions, and callable methods and method calls. Whereas interfaces automata have a refinement relation, we argue the crucial relation in pervasive systems is component replacement, which must include consideration of the services offered by a component and assumptions about the environment. We illustrate pervasive interface autmotata and component replacement with a small case study of a pervasive application for sports predictions
An Improvement of the Piggyback Algorithm for Parallel Model Checking
This paper extends the piggyback algorithm to enlarge the set of liveness properties it can verify. Its extension is motivated by an attempt to express in logic the counterexamples it can detect and relate them to bounded liveness. The original algorithm is based on parallel breadth-first search and piggybacking of accepting states that are deleted after counting a fixed number of transitions. The main improvement is obtained by renewing the counter of transitions when the same accepting states are visited in the negated property automaton. In addition, we describe piggybacking of multiple states in either sets (exact) or Bloom filters (lossy but conservative), and use of local searches that attempt to connect cycles fragmented among processing cores. Finally it is proved that accepting cycle detection is in NC in the size of the product automaton's entire state space, including unreachable states
BioDiVinE: A Framework for Parallel Analysis of Biological Models
In this paper a novel tool BioDiVinEfor parallel analysis of biological
models is presented. The tool allows analysis of biological models specified in
terms of a set of chemical reactions. Chemical reactions are transformed into a
system of multi-affine differential equations. BioDiVinE employs techniques for
finite discrete abstraction of the continuous state space. At that level,
parallel analysis algorithms based on model checking are provided. In the
paper, the key tool features are described and their application is
demonstrated by means of a case study
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
Variations on Multi-Core Nested Depth-First Search
Recently, two new parallel algorithms for on-the-fly model checking of LTL
properties were presented at the same conference: Automated Technology for
Verification and Analysis, 2011. Both approaches extend Swarmed NDFS, which
runs several sequential NDFS instances in parallel. While parallel random
search already speeds up detection of bugs, the workers must share some global
information in order to speed up full verification of correct models. The two
algorithms differ considerably in the global information shared between
workers, and in the way they synchronize.
Here, we provide a thorough experimental comparison between the two
algorithms, by measuring the runtime of their implementations on a multi-core
machine. Both algorithms were implemented in the same framework of the model
checker LTSmin, using similar optimizations, and have been subjected to the
full BEEM model database.
Because both algorithms have complementary advantages, we constructed an
algorithm that combines both ideas. This combination clearly has an improved
speedup. We also compare the results with the alternative parallel algorithm
for accepting cycle detection OWCTY-MAP. Finally, we study a simple statistical
model for input models that do contain accepting cycles. The goal is to
distinguish the speedup due to parallel random search from the speedup that can
be attributed to clever work sharing schemes.Comment: In Proceedings PDMC 2011, arXiv:1111.006
Conservation of freshwater bivalves at the global scale: diversity, threats and research needs
Bivalves are ubiquitous members of freshwater ecosystems and responsible for important functions and services. The present paper revises freshwater bivalve diversity, conservation status and threats at the global scale and discusses future research needs and management actions. The diversity patterns are uneven across the globe with hotspots in the interior basin in the United States of America (USA), Central America, Indian subcontinent and Southeast Asia. Freshwater bivalves are affected by multiple threats that vary across the globe; however, pollution and natural system (habitat) modifications being consistently found as the most impacting. Freshwater bivalves are among the most threatened groups in the world with 40% of the species being near threatened, threatened or extinct, and among them the order Unionida is the most endangered. We suggest that global cooperation between scientists, managers, politicians and general public, and application of new technologies (new generation sequencing and remote sensing, among others) will strengthen the quality of studies on the natural history and conservation of freshwater bivalves. Finally, we introduce the articles published in this special issue of Hydrobiologia under the scope of the Second International Meeting on Biology and Conservation of Freshwater Bivalves held in 2015 in Buffalo, New York, USA.This work was supported by FCT—Foundation for Science and
Technology, Project 3599—Promote the Scientific Production
and Technological Development and Thematic 3599-PPCDT by
FEDER as part of the project FRESHCO: multiple implications
of invasive species on Freshwater Mussel co-extinction
processes (Contract: PTDC/AGRFOR/1627/2014). FCT also
supported MLL under Grant (SFRH/BD/115728/2016)
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