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SUMMARY:ENBIS/JMP webinar: Test Selection as a Design of Experiments Probl
 em
DTSTART:20261105T140000Z
DTEND:20261105T150000Z
DTSTAMP:20261028T093200Z
UID:indico-event-95@conferences.enbis.org
DESCRIPTION:\n\nTest Selection as a Design of Experiments Problem\nSpeaker
 : \nRyan Lekivetz (JMP\, Director of Advanced Analytics R&D)\nDate: Nov 5
 th\, 3 pm CET\nAbstract:\nTesting complex systems presents unique challeng
 es. The space of possible inputs\, options\, configurations\, and workflow
 s can be enormous\, making exhaustive testing impractical. At the same tim
 e\, developers and users often have limited time and resources for formal 
 testing activities.\nThis talk explores how principles from Design of Expe
 riments (DOE) can be applied to the test case selection problem. By viewin
 g test cases as experimental runs and system inputs as factors\, DOE provi
 des a structured framework for constructing efficient test suites that max
 imize information while minimizing effort. The discussion highlights conne
 ctions between experimental design and software testing\, demonstrating ho
 w statistical thinking can improve test coverage\, identify defects more e
 ffectively\, and increase confidence in system reliability.\nExamples are 
 drawn primarily from statistical software testing\, but the same ideas app
 ly more broadly to other complex systems\, including AI tools and large la
 nguage models\, where interactions among inputs can create an overwhelming
  number of possible test scenarios.\n \nBio:\n\nRyan Lekivetz is a Direct
 or of Advanced Analytics R&D at JMP\, heading the Design of Experiments (D
 OE) and Reliability Development team. Lekivetz earned his doctorate in sta
 tistics from Simon Fraser University in Burnaby\, British Columbia. He has
  published papers on DOE topics in peer-reviewed journals and holds many p
 atents that he shares with his team members.\n \n \n \n\n \n\nhttps://
 conferences.enbis.org/event/95/
URL:https://conferences.enbis.org/event/95/
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