An Experimental Spatio-Temporal Model Checker

Ciancia, Vincenzo; Grilletti, Gianluca; Latella, Diego; Loreti, Michele; Massink, Mieke

doi:10.1007/978-3-662-49224-6_24

Cited by 36 publications

(28 citation statements)

References 7 publications

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“…A great deal of possibilities are explored in [31], for spatial logics based on topological spaces. One such structure was explored in [13,26], in the setting of closure spaces. The current implementation is provided by the open source spatio-temporal model checker 4 topochecker, that can verify formulas written in the spatio-temporal logic of closure spaces STLCS.…”

Section: Possible Points Diverted Bus Positions Are Represented By Thmentioning

confidence: 99%

“…In this section we provide a lightweight informal introduction to spatio-temporal model checking; we refer the interested reader to [13] for further technical details. Like SLCS, this spatio-temporal logic is developed in the setting of closure spaces.…”

Section: Possible Points Diverted Bus Positions Are Represented By Thmentioning

confidence: 99%

“…Besides the purely spatial aspects, we also illustrate the use of model-checking to detect operational problems of the bus network. We use the spatio-temporal model-checker developed in [13], extending the spatial model checker of [14,15] with temporal features. The temporal fragment is developed as a variant of the well-known Computation Tree Logic (CTL).…”

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confidence: 99%

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Spatio-temporal model checking of vehicular movement in public transport systems

Ciancia

Gilmore

Grilletti

et al. 2018

Int J Softw Tools Technol Transfer

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We present the use of a novel spatio-temporal model-checker to detect problems in the data and operation of a collective adaptive system. Data correctness is important to ensure operational correctness in systems which adapt in response to data. We illustrate the theory with several concrete examples, addressing both the detection of errors in vehicle location data for buses in the city of Edinburgh and the undesirable phenomenon of "clumping" which occurs when there is not enough separation between subsequent buses serving the same route. Vehicle location data is visualised symbolically on a street map, and categories of problems identified by the spatial part of the model-checker are rendered by highlighting the symbols for vehicles or other objects that satisfy a property of interest. Behavioural correctness makes use of both the spatial and temporal aspects of the model-checker to determine from a series of observations of vehicle locations whether the system is failing to meet the expected quality of service demanded by system regulators.

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Section: Possible Points Diverted Bus Positions Are Represented By Thmentioning

confidence: 99%

Section: Possible Points Diverted Bus Positions Are Represented By Thmentioning

confidence: 99%

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Spatio-temporal model checking of vehicular movement in public transport systems

Ciancia

Gilmore

Grilletti

et al. 2018

Int J Softw Tools Technol Transfer

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“…We finally introduced an efficient model-checking procedure and produced an implementation of a spatial model-checker called topochecker; the tool is able to interpret spatial logics on generic graphs including digital images, providing graphical understanding of the meaning of formulae, and an immediate form of counterexample visualisation. In [9] the logic and the modelchecking procedure have been extended with classical temporal logic operators so that a spatio-temporal logic and model-checking tool is now available for reasoning about dynamically changing spaces give rise. For example, one can characterise those points which will eventually be surrounded by points which may eventually be close to points satisfying φ .…”

Section: Automatic Reasoning About Spacementioning

confidence: 99%

On Formal Methods for Collective Adaptive System Engineering. Scalable Approximated, Spatial Analysis Techniques. Extended Abstract.

Latella

2016

Electron. Proc. Theor. Comput. Sci.

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In this extended abstract a view on the role of Formal Methods in System Engineering is briefly presented. Then two examples of useful analysis techniques based on solid mathematical theories are discussed as well as the software tools which have been built for supporting such techniques. The first technique is Scalable Approximated Population DTMC Model-checking. The second one is Spatial Model-checking for Closure Spaces. Both techniques have been developed in the context of the EU funded project QUANTICOL. * Work partially funded by the EU projects QUANTICOL (nr. 600708) and ASCENS (nr. 257414).

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“…In recent work [18,19], Ciancia et al pushed such theoretical development further to encompass directed graphs, resulting in the definition of the Spatial Logic for Closure Spaces (SLCS), and a related model checking algorithm. Subsequently, in [17], a spatio-temporal logic, combining Computation Tree Logic and the newly defined spatial operators, was introduced; the (extended) model checking algorithm has been implemented in the prototype spatio-temporal model checker topochecker 1 .…”

Section: Introductionmentioning

confidence: 99%

Spatial logics and model checking for medical imaging

Buonamici

Belmonte

Ciancia

et al. 2019

Int J Softw Tools Technol Transfer

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Recent research on spatial and spatio-temporal model checking provides novel image analysis methodologies, rooted in logical methods for topological spaces. Medical Imaging (MI) is a field where such methods show potential for ground-breaking innovation. Our starting point is SLCS, the Spatial Logic for Closure Spaces-Closure Spaces being a generalisation of topological spaces, covering also discrete space structuresand topochecker, a model-checker for SLCS (and extensions thereof). We introduce the logical language ImgQL ("Image Query Language"). ImgQL extends SLCS with logical operators describing distance and region similarity. The spatio-temporal model checker topochecker is correspondingly enhanced with state-of-the-art algorithms, borrowed from computational image processing, for efficient implementation of distancebased operators, namely distance transforms. Similarity between regions is defined by means of a statistical similarity operator, based on notions from statistical texture analysis. We illustrate our approach by means of two examples of analysis of Magnetic Resonance images: segmentation of glioblastoma and its oedema, and segmentation of rectal carcinoma.

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An Experimental Spatio-Temporal Model Checker

Cited by 36 publications

References 7 publications

Spatio-temporal model checking of vehicular movement in public transport systems

Spatio-temporal model checking of vehicular movement in public transport systems

On Formal Methods for Collective Adaptive System Engineering. Scalable Approximated, Spatial Analysis Techniques. Extended Abstract.

Spatial logics and model checking for medical imaging

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