42,622 research outputs found
Verification of Query Completeness over Processes [Extended Version]
Data completeness is an essential aspect of data quality, and has in turn a
huge impact on the effective management of companies. For example, statistics
are computed and audits are conducted in companies by implicitly placing the
strong assumption that the analysed data are complete. In this work, we are
interested in studying the problem of completeness of data produced by business
processes, to the aim of automatically assessing whether a given database query
can be answered with complete information in a certain state of the process. We
formalize so-called quality-aware processes that create data in the real world
and store it in the company's information system possibly at a later point.Comment: Extended version of a paper that was submitted to BPM 201
Query Stability in Monotonic Data-Aware Business Processes [Extended Version]
Organizations continuously accumulate data, often according to some business
processes. If one poses a query over such data for decision support, it is
important to know whether the query is stable, that is, whether the answers
will stay the same or may change in the future because business processes may
add further data. We investigate query stability for conjunctive queries. To
this end, we define a formalism that combines an explicit representation of the
control flow of a process with a specification of how data is read and inserted
into the database. We consider different restrictions of the process model and
the state of the system, such as negation in conditions, cyclic executions,
read access to written data, presence of pending process instances, and the
possibility to start fresh process instances. We identify for which facet
combinations stability of conjunctive queries is decidable and provide
encodings into variants of Datalog that are optimal with respect to the
worst-case complexity of the problem.Comment: This report is the extended version of a paper accepted at the 19th
International Conference on Database Theory (ICDT 2016), March 15-18, 2016 -
Bordeaux, Franc
The Construction of Verification Models for Embedded Systems
The usefulness of verification hinges on the quality of the verification model. Verification is useful if it increases our confidence that an artefact bahaves as expected. As modelling inherently contains non-formal elements, the qualityof models cannot be captured by purely formal means. Still, we argue that modelling is not an act of irrationalism and unpredictable geniality, but follows rational arguments, that often remain implicit. In this paper we try to identify the tacit rationalism in the model construction as performed by most people doing modelling for verification. By explicating the different phases, arguments, and design decisions in the model construction, we try to develop guidelines that help to improve the process of model construction and the quality of models
Focused Proofreading: Efficiently Extracting Connectomes from Segmented EM Images
Identifying complex neural circuitry from electron microscopic (EM) images
may help unlock the mysteries of the brain. However, identifying this circuitry
requires time-consuming, manual tracing (proofreading) due to the size and
intricacy of these image datasets, thus limiting state-of-the-art analysis to
very small brain regions. Potential avenues to improve scalability include
automatic image segmentation and crowd sourcing, but current efforts have had
limited success. In this paper, we propose a new strategy, focused
proofreading, that works with automatic segmentation and aims to limit
proofreading to the regions of a dataset that are most impactful to the
resulting circuit. We then introduce a novel workflow, which exploits
biological information such as synapses, and apply it to a large dataset in the
fly optic lobe. With our techniques, we achieve significant tracing speedups of
3-5x without sacrificing the quality of the resulting circuit. Furthermore, our
methodology makes the task of proofreading much more accessible and hence
potentially enhances the effectiveness of crowd sourcing
A System for Deduction-based Formal Verification of Workflow-oriented Software Models
The work concerns formal verification of workflow-oriented software models
using deductive approach. The formal correctness of a model's behaviour is
considered. Manually building logical specifications, which are considered as a
set of temporal logic formulas, seems to be the significant obstacle for an
inexperienced user when applying the deductive approach. A system, and its
architecture, for the deduction-based verification of workflow-oriented models
is proposed. The process of inference is based on the semantic tableaux method
which has some advantages when compared to traditional deduction strategies.
The algorithm for an automatic generation of logical specifications is
proposed. The generation procedure is based on the predefined workflow patterns
for BPMN, which is a standard and dominant notation for the modeling of
business processes. The main idea for the approach is to consider patterns,
defined in terms of temporal logic,as a kind of (logical) primitives which
enable the transformation of models to temporal logic formulas constituting a
logical specification. Automation of the generation process is crucial for
bridging the gap between intuitiveness of the deductive reasoning and the
difficulty of its practical application in the case when logical specifications
are built manually. This approach has gone some way towards supporting,
hopefully enhancing our understanding of, the deduction-based formal
verification of workflow-oriented models.Comment: International Journal of Applied Mathematics and Computer Scienc
Model Driven Mutation Applied to Adaptative Systems Testing
Dynamically Adaptive Systems modify their behav- ior and structure in
response to changes in their surrounding environment and according to an
adaptation logic. Critical sys- tems increasingly incorporate dynamic
adaptation capabilities; examples include disaster relief and space exploration
systems. In this paper, we focus on mutation testing of the adaptation logic.
We propose a fault model for adaptation logics that classifies faults into
environmental completeness and adaptation correct- ness. Since there are
several adaptation logic languages relying on the same underlying concepts, the
fault model is expressed independently from specific adaptation languages.
Taking benefit from model-driven engineering technology, we express these
common concepts in a metamodel and define the operational semantics of mutation
operators at this level. Mutation is applied on model elements and model
transformations are used to propagate these changes to a given adaptation
policy in the chosen formalism. Preliminary results on an adaptive web server
highlight the difficulty of killing mutants for adaptive systems, and thus the
difficulty of generating efficient tests.Comment: IEEE International Conference on Software Testing, Verification and
Validation, Mutation Analysis Workshop (Mutation 2011), Berlin : Allemagne
(2011
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