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UID:20261030T081903EDT-4526TacS5m@132.216.98.100
DTSTAMP:20261030T121903Z
DESCRIPTION: \n\nTitle:\n\nApplying DOE Principles to Statistical Software 
 Testing.\n\nAbstract:\n\nTesting statistical software presents unique chal
 lenges. The space of possible inputs\, options\, and workflows can be enor
 mous\, making exhaustive testing impractical. At the same time\, software 
 developers often have limited time and resources for formal testing activi
 ties.\n\nThis talk explores how principles from Design of Experiments (DOE
 ) can be applied to the software test case selection problem. By viewing t
 est cases as experimental runs and software inputs as factors\, DOE provid
 es a structured framework for constructing efficient test suites that maxi
 mize information while minimizing effort. The discussion highlights connec
 tions between experimental design and software testing\, demonstrating how
  statistical thinking can improve test coverage\, identify defects more ef
 fectively\, and increase confidence in software reliability. More broadly\
 , the talk illustrates how core ideas from DOE can be successfully applied
  in nontraditional settings.\n\nSpeaker\n\nRyan Lekivetz is a Director of 
 Advanced Analytics R&D at JMP\, heading the Design of Experiments (DOE) an
 d Reliability Development team. Lekivetz earned his doctorate in statistic
 s from Simon Fraser University in Burnaby\, British Columbia. He has publi
 shed papers on DOE topics in peer-reviewed journals and holds many patents
  that he shares with his team members.\n\nhttps://mcgill.zoom.us/j/8251083
 7324\n\nMeeting ID: 825 1083 7324\n
DTSTART:20261030T193000Z
DTEND:20261030T203000Z
LOCATION:Room 1104\, Burnside Hall\, CA\, QC\, Montreal\, H3A 0B9\, 805 rue
  Sherbrooke Ouest
SUMMARY:Ryan Lekivetz from JMP
URL:https://www.mcgill.ca/mathstat/channels/event/ryan-lekivetz-jmp-375244
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