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AI and Machine Learning for Testers Jason Arbon, CEO @Appdiff - PowerPoint PPT Presentation

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AI and Machine Learning for Testers Jason Arbon, CEO @Appdiff Relevant Context Testing Neural Net Ranker Personalized Web Search and Chrome Test Automation AI for Mobile Test Automation Ai for Test 2 Automation Agenda AI For Testing

  1. AI and Machine Learning for Testers Jason Arbon, CEO @Appdiff

  2. Relevant Context Testing Neural Net Ranker Personalized Web Search and Chrome Test Automation AI for Mobile Test Automation Ai for Test 2 Automation

  3. Agenda AI For Testing Testing AI Future Ai for Test Automation

  4. The Real Data Scientists Joanne Tseng Data Scientist @appdiff.com Appdiff mission: Transform app development with Francis Iannacci automation & insights Lead Data Scientist @appdiff.com 4 Appdiff Presentation

  5. Testing: Apply Inputs, checking outputs. 5 Testing is much like AI

  6. AI: Apply Inputs, check outputs https://www.extremetech.com/extreme/215170-artificial-neural-networks-are- 6 changing-the-world-what-are-they

  7. Testing Needs AI Features Complexity increases Complexity / Coverage exponentially as new features and states interact with existing COVERAGE features GAP Tests Test coverage grows linearly because tests can only be added one at a time Time 7 AI for App Testing

  8. Definition 8 Our Story

  9. When will AI Start Testing?

  10. AI for Testing 10 Our Story

  11. ML : Subjective or complex labels via Humans 11 What We Do

  12. AI for Testing: Input Reduce input space 150 actions per page 35 steps -> 150^35 = 10^78 paths #atoms in universe 10^78... 12 Our Story

  13. AI for Testing 13 Our Story

  15. AI for Testing 15 Our Story

  16. AI Driven Test Flows 16 Our Story

  17. AI Driven Test Flows 17 Our Story

  18. AI Driven Test Flows 18 Our Story

  19. Coverage 19 Our Story

  20. Coverage

  21. ML : App Changes Don’t Break Bot Testing! 21 What We Do

  22. AI bots can test almost any app. 10,000+ apps tested. 22 Our Story

  23. Testing the Conference App 23 Our Story

  24. Benchmarked Performance 24 Our Story

  25. portfolio

  26. Current AI Coverage: ~2/3rds Existing Tests Long Sequences of Dependant Actions and Verifications Basic Tasks (Login, Search, Create Account, Add items to Card, etc.) Specific Sequences of Events with Specific Input (search for ‘beanie babies’, etc.) 26 AI for Testing

  27. Automation Coverage: Bots soon 100% 27 AI for Testing

  28. Automation Coverage: Bots... soon after, 10X Canonical Tests Learning Tests Cross-app 28 AI for Testing

  29. Testing AI: Test Graph Generation and Traversal 29 Our Story

  30. Testing Flow with AI 30 What We Do

  31. Abstract Intent Language: AIT Focus on Intent, not “how” Human Readable App-Independant 31 What We Do

  32. AI for Testing 32 Our Story

  33. QnA hi@appdiff.com Jason Arbon, CEO jason@appdiff.com

  34. Appendix

  35. ML: Page Label Training 35 What We Do

  36. Appdiff Represents the Evolution of Software Quality Automation QA QA App App App 1 2 3 4 AD HOC MANUAL TEST AI-DRIVEN TESTING TESTING AUTOMATION APPROACH Reactively test Proactively test Automate repetition Accelerate coverage 36 Our Story

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