Crowd Testing in the Wild for COVID Contact Tracing
W5 Start Time : 11:15 End Time : 11:45
Testing in the wild journey, helping to fight the spread of COVID-19 working with MIT and global team volunteers to build and test a privacy-first, citizen-led contact tracing platform to save lives.
Join Jonathon, as he explores the challenges of testing contact tracing such as location data utilising multiple technologies like GPS and Bluetooth. The importance of privacy and transparency to build trust in Medical Privacy and how to synthetically generate and anonymise test location data.
Exploring experimental test approaches and techniques:
- Global Crowd Testing – Coordinating thousands of volunteers.
- Digital Experience Analytics – Next Generation (In-App) Telemetrics provide feedback of real user journeys then automatically generate model-based testing (MBT).
- Shift Right / Digital Twin – Leveraging real world models with Visual Testing capabilities based on image-based testing (IBT) to execute journeys across multiple-platforms such as Data Visualisation Tools, Google Takeout & two-factor authentication.
- Dark Launching & Canary Rollouts (A/B Testing) – Validation of controlled test experiments in production and staging (TestFlight) to validate Digital Experiences (DX).
- Model-based Data (MBD) – Test Data Automation techniques to synthetically generate 5 billion historical location data points to cover all possible paths and multi-modal transportation categories.
Key Takeaways:
- Shifting Up – How to rapidly validate an idea (hypothesis) from the business (before writing a single line of code)
- Shifting Down – How to rapidly test an idea (crowd testing) on real users throughout the delivery life-cycle (qualitative & quantitative)
- Shifting Right – How to validate an idea (real user behavior) in production is a success (engagement & conversion goals) and create MBT of real user journeys
Speaker
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W5 Start Time : 11:15 End Time : 11:45
Testing in the wild journey, helping to fight the spread of COVID-19 working with MIT and global team volunteers to build and test a privacy-first, citizen-led contact tracing platform to save lives.
Join Jonathon, as he explores the challenges of testing contact tracing such as location data utilising multiple technologies like GPS and Bluetooth. The importance of privacy and transparency to build trust in Medical Privacy and how to synthetically generate and anonymise test location data.
Exploring experimental test approaches and techniques:
- Global Crowd Testing – Coordinating thousands of volunteers.
- Digital Experience Analytics – Next Generation (In-App) Telemetrics provide feedback of real user journeys then automatically generate model-based testing (MBT).
- Shift Right / Digital Twin – Leveraging real world models with Visual Testing capabilities based on image-based testing (IBT) to execute journeys across multiple-platforms such as Data Visualisation Tools, Google Takeout & two-factor authentication.
- Dark Launching & Canary Rollouts (A/B Testing) – Validation of controlled test experiments in production and staging (TestFlight) to validate Digital Experiences (DX).
- Model-based Data (MBD) – Test Data Automation techniques to synthetically generate 5 billion historical location data points to cover all possible paths and multi-modal transportation categories.
Key Takeaways:
- Shifting Up – How to rapidly validate an idea (hypothesis) from the business (before writing a single line of code)
- Shifting Down – How to rapidly test an idea (crowd testing) on real users throughout the delivery life-cycle (qualitative & quantitative)
- Shifting Right – How to validate an idea (real user behavior) in production is a success (engagement & conversion goals) and create MBT of real user journeys