9,250 research outputs found
Artificial table testing dynamically adaptive systems
Dynamically Adaptive Systems (DAS) are systems that modify their behavior and
structure in response to changes in their surrounding environment. Critical
mission systems increasingly incorporate adaptation and response to the
environment; examples include disaster relief and space exploration systems.
These systems can be decomposed in two parts: the adaptation policy that
specifies how the system must react according to the environmental changes and
the set of possible variants to reconfigure the system. A major challenge for
testing these systems is the combinatorial explosions of variants and
envi-ronment conditions to which the system must react. In this paper we focus
on testing the adaption policy and propose a strategy for the selection of
envi-ronmental variations that can reveal faults in the policy. Artificial
Shaking Table Testing (ASTT) is a strategy inspired by shaking table testing
(STT), a technique widely used in civil engineering to evaluate building's
structural re-sistance to seismic events. ASTT makes use of artificial
earthquakes that simu-late violent changes in the environmental conditions and
stresses the system adaptation capability. We model the generation of
artificial earthquakes as a search problem in which the goal is to optimize
different types of envi-ronmental variations
CHORUS Deliverable 2.1: State of the Art on Multimedia Search Engines
Based on the information provided by European projects and national initiatives related to multimedia search as well as domains experts that participated in the CHORUS Think-thanks and workshops, this document reports on the state of the art related to multimedia content search from, a technical, and socio-economic perspective.
The technical perspective includes an up to date view on content based indexing and retrieval technologies, multimedia search in the context of mobile devices and peer-to-peer networks, and an overview of current evaluation and benchmark inititiatives to measure the performance of multimedia search engines.
From a socio-economic perspective we inventorize the impact and legal consequences of these technical advances and point out future directions of research
Stochastic Query Covering for Fast Approximate Document Retrieval
We design algorithms that, given a collection of documents and a distribution over user queries, return a
small subset of the document collection in such a way that we can efficiently provide high-quality answers
to user queries using only the selected subset. This approach has applications when space is a constraint
or when the query-processing time increases significantly with the size of the collection. We study our
algorithms through the lens of stochastic analysis and prove that even though they use only a small fraction
of the entire collection, they can provide answers to most user queries, achieving a performance close to the
optimal. To complement our theoretical findings, we experimentally show the versatility of our approach
by considering two important cases in the context of Web search. In the first case, we favor the retrieval of
documents that are relevant to the query, whereas in the second case we aim for document diversification.
Both the theoretical and the experimental analysis provide strong evidence of the potential value of query
covering in diverse application scenarios
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