18,897 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
Abstract Interpretation of Stateful Networks
Modern networks achieve robustness and scalability by maintaining states on
their nodes. These nodes are referred to as middleboxes and are essential for
network functionality. However, the presence of middleboxes drastically
complicates the task of network verification. Previous work showed that the
problem is undecidable in general and EXPSPACE-complete when abstracting away
the order of packet arrival.
We describe a new algorithm for conservatively checking isolation properties
of stateful networks. The asymptotic complexity of the algorithm is polynomial
in the size of the network, albeit being exponential in the maximal number of
queries of the local state that a middlebox can do, which is often small.
Our algorithm is sound, i.e., it can never miss a violation of safety but may
fail to verify some properties. The algorithm performs on-the fly abstract
interpretation by (1) abstracting away the order of packet processing and the
number of times each packet arrives, (2) abstracting away correlations between
states of different middleboxes and channel contents, and (3) representing
middlebox states by their effect on each packet separately, rather than taking
into account the entire state space. We show that the abstractions do not lose
precision when middleboxes may reset in any state. This is encouraging since
many real middleboxes reset, e.g., after some session timeout is reached or due
to hardware failure
HBST: A Hamming Distance embedding Binary Search Tree for Visual Place Recognition
Reliable and efficient Visual Place Recognition is a major building block of
modern SLAM systems. Leveraging on our prior work, in this paper we present a
Hamming Distance embedding Binary Search Tree (HBST) approach for binary
Descriptor Matching and Image Retrieval. HBST allows for descriptor Search and
Insertion in logarithmic time by exploiting particular properties of binary
Feature descriptors. We support the idea behind our search structure with a
thorough analysis on the exploited descriptor properties and their effects on
completeness and complexity of search and insertion. To validate our claims we
conducted comparative experiments for HBST and several state-of-the-art methods
on a broad range of publicly available datasets. HBST is available as a compact
open-source C++ header-only library.Comment: Submitted to IEEE Robotics and Automation Letters (RA-L) 2018 with
International Conference on Intelligent Robots and Systems (IROS) 2018
option, 8 pages, 10 figure
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