Date: 2026-10-30

Time: 15:30-16:30 (Montreal time)

Location: In person, Burnside 1104

https://mcgill.zoom.us/j/82510837324

Meeting ID: 825 1083 7324

Abstract:

Testing statistical software presents unique challenges. The space of possible inputs, options, and workflows can be enormous, making exhaustive testing impractical. At the same time, software developers often have limited time and resources for formal testing activities.

This talk explores how principles from Design of Experiments (DOE) can be applied to the software test case selection problem. By viewing test cases as experimental runs and software inputs as factors, DOE provides a structured framework for constructing efficient test suites that maximize information while minimizing effort. The discussion highlights connections between experimental design and software testing, demonstrating how statistical thinking can improve test coverage, identify defects more effectively, and increase confidence in software reliability. More broadly, the talk illustrates how core ideas from DOE can be successfully applied in nontraditional settings.

Speaker

Ryan Lekivetz is a Director of Advanced Analytics R&D at JMP, heading the Design of Experiments (DOE) and Reliability Development team. Lekivetz earned his doctorate in statistics from Simon Fraser University in Burnaby, British Columbia. He has published papers on DOE topics in peer-reviewed journals and holds many patents that he shares with his team members.