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O que (quem) é Data Driven Machine - definição

DDDAS; Dynamic Data Driven Application Simulation; Dynamic Data Driven Application System; Dynamic data driven application system; Dynamic data-driven application system; Dynamic data driven application systems; Dynamic data driven applications systems; Dynamic Data Driven Applications Systems - (DDDAS)

Data Driven Machine

<language> (DDM) A dataflow language. ["The Architecture and System Method of DDM-1: A Recursively Structured Data Driven Machine", A. Davis, Proc 5th Ann Symp Comp Arch, IEEE 1978]. (1999-04-26)

Data-driven testing

SOFTWARE TESTING METHODOLOGY THAT IS USED IN THE TESTING OF COMPUTER SOFTWARE TO DESCRIBE TESTING DONE USING A TABLE OF CONDITIONS DIRECTLY AS TEST INPUTS AND VERIFIABLE OUTPUTS

Data-Driven Testing; Parameterized test; Parameterized testing

Data-driven testing (DDT), also known as table-driven testing or parameterized testing, is a software testing methodology that is used in the testing of computer software to describe testing done using a table of conditions directly as test inputs and verifiable outputs as well as the process where test environment settings and control are not hard-coded. In the simplest form the tester supplies the inputs from a row in the table and expects the outputs which occur in the same row.

https://en.wikipedia.org/wiki/Data-driven_testing

Data science

INTERDISCIPLINARY FIELD OF STUDY FOCUSED ON DERIVING KNOWLEDGE AND INSIGHTS FROM DATA

Data driven science; Data-driven science; Wikipedia talk:Articles for creation/Data Science; Data scientist; Security data science; Data scientists; Data Science; Data duck; History of data science

Data science is an interdisciplinary field that uses scientific methods, processes, algorithms and systems to extract or extrapolate knowledge and insights from noisy, structured and unstructured data, and apply knowledge from data across a broad range of application domains. Data science is related to data mining, machine learning and big data.

https://en.wikipedia.org/wiki/Data_science

Wikipédia

Dynamic Data Driven Applications Systems

Dynamic Data Driven Applications Systems (DDDAS) is a new paradigm whereby the computation and instrumentation aspects of an application system are dynamically integrated in a feed-back control loop, in the sense that instrumentation data can be dynamically incorporated into the executing model of the application, and in reverse the executing model can control the instrumentation. Such approaches have been shown that can enable more accurate and faster modeling and analysis of the characteristics and behaviors of a system and can exploit data in intelligent ways to convert them to new capabilities, including decision support systems with the accuracy of full scale modeling, efficient data collection, management, and data mining. The DDDAS concept - and the term - was proposed by Frederica Darema for the National Science Foundation (NSF) workshop in March 2000.

There are several affiliated annual meetings and conferences, including:

DDDAS workshop at ICCS (since 2003)
DyDESS conference and workshop at MIT organized by Sai Ravela and Adrian Sandu
DDDAS special session at the ACC organized by Puneet Singla and Dennis Bernstein and Sai Ravela
DDDAS Special Session Information Fusion

https://en.wikipedia.org/wiki/Dynamic Data Driven Applications Systems