Model Based Testing Shifting Right into the Real World
summary
Model-based testing shifts right into production by building executable environment models and feeding real-device signals to them. A MIT contact-tracing/vaccine-passport effort assembles a digital twin in five hours, generates 2 billion synthetic transactions from Google Takeout data, and explores about 9,500 routes through GPS then GAEN Bluetooth paths. Tooling includes Appium, Splunk-derived digital experience analytics, Dynatrace Captain and OpenTelemetry, enabling canary/A-B runs in prod and tuning that measurably reduces false positives.
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chapters (22)
- 0:00Intro
- 3:07Model Based Testing
- 8:15What are symptoms
- 9:47Algorithm
- 11:10Machine Learning
- 12:43Data Engineering
- 14:17New Model for Testing
- 15:50Digital Twin
- 18:25MIT App
- 19:31Data Source
- 21:35Privacy by Design
- 25:40Augmented Reality
- 27:20Changing the Way We Think
- 29:03Context Switching
- 29:49Digital Burnout
- 31:30The Metaverse
- 32:15Amazon
- 33:15Fallout
- 34:00Complexity
- 34:20Silos
- 36:05Community
- 36:45Tools
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