Difference between revisions of "Review:RTE"

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== Robust Testing Environments (RTE) ==
 
== Robust Testing Environments (RTE) ==
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[[File:test.pdf]]
  
 
Currently much time is spent in setting up system tests, trying to understand exactly what is being tested, understanding errors that occur during tests and verifying the test results. These issues can be especially difficult for distributed enterprise applications made up of a large number of software components that run on a collection of heterogeneous servers or in cloud environments. Load generation for accurate simulation of complex user behaviour is a growing challenge when testing large-scale critical systems. For example, with more and more applications moving to cloud-based infrastructures, typical load generation designed for applications residing on a local area network may be ineffective for robust testing. Research is required to develop new load generation techniques that take into consideration new cloud-based infrastructures where applications may be physically distributed across different infrastructures in different geographical locations and where network bandwidth may be unknown or at different quality levels at various points. This research will develop a set of prototype tools to allow for the more efficient system testing of large enterprise applications.  
 
Currently much time is spent in setting up system tests, trying to understand exactly what is being tested, understanding errors that occur during tests and verifying the test results. These issues can be especially difficult for distributed enterprise applications made up of a large number of software components that run on a collection of heterogeneous servers or in cloud environments. Load generation for accurate simulation of complex user behaviour is a growing challenge when testing large-scale critical systems. For example, with more and more applications moving to cloud-based infrastructures, typical load generation designed for applications residing on a local area network may be ineffective for robust testing. Research is required to develop new load generation techniques that take into consideration new cloud-based infrastructures where applications may be physically distributed across different infrastructures in different geographical locations and where network bandwidth may be unknown or at different quality levels at various points. This research will develop a set of prototype tools to allow for the more efficient system testing of large enterprise applications.  

Revision as of 17:50, 10 May 2013

<accesscontrol>reviewer,pel</accesscontrol>

Robust Testing Environments (RTE)

File:Test.pdf

Currently much time is spent in setting up system tests, trying to understand exactly what is being tested, understanding errors that occur during tests and verifying the test results. These issues can be especially difficult for distributed enterprise applications made up of a large number of software components that run on a collection of heterogeneous servers or in cloud environments. Load generation for accurate simulation of complex user behaviour is a growing challenge when testing large-scale critical systems. For example, with more and more applications moving to cloud-based infrastructures, typical load generation designed for applications residing on a local area network may be ineffective for robust testing. Research is required to develop new load generation techniques that take into consideration new cloud-based infrastructures where applications may be physically distributed across different infrastructures in different geographical locations and where network bandwidth may be unknown or at different quality levels at various points. This research will develop a set of prototype tools to allow for the more efficient system testing of large enterprise applications.

Quarter Deliverables Files
Q2 2012 Survey of data mining algorithms. Slides
Q3 2012 Initial algorithm to automatically extract relationships between schemas in a DB ICUIMC
Q1 2013 Survey of algorithms for database sampling.
Design and specification of an algorithm for database sampling (table-level)
DEXA
Mar 2012 Specification of algorithms for robust load generation
Jun 2012 Design of data set generation tool