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Mining App Store requirements Mark Harman, Yue Jia and Yuanyuan Zhang University College London Mining App Store requirements Mark Harman, Yue Jia and Yuanyuan Zhang University College London Motivation Customer Customer A B R 3 R 1


  1. Mining App Store requirements Mark Harman, Yue Jia and Yuanyuan Zhang University College London

  2. Mining App Store requirements Mark Harman, Yue Jia and Yuanyuan Zhang University College London

  3. Motivation Customer Customer A B R 3 R 1 R 4 R 2 R 5

  4. Bugs S V N B u g Git z i l l a Traditional Software Repository MSR for App Stores

  5. Bugs Email Source Code Changes Technical Reports S V N B u g Git z i l l a Traditional Software Repository MSR for App Stores

  6. Bugs Email Source Code Changes Technical Reports S V N B u g Git z i l l a Traditional Software Repository MSR for App Stores

  7. Bugs Email Source Code Changes Technical Reports Customer S V N B u g Git z i l l a Traditional Software Business Repository MSR for App Stores

  8. App Store Repository MSR for App Stores

  9. Ratings Popularity Customer App Store Repository Price Business MSR for App Stores

  10. Features Technical Ratings Popularity Customer App Store Repository Price Business MSR for App Stores

  11. MSR for App Stores

  12. MSR for App Stores

  13. MSR for App Stores

  14. MSR for App Stores

  15. MSR for App Stores

  16. MSR for App Stores http://www.cs.ucl.ac.uk/staff/Y.Jia/projects/app_store_mining

  17. MSR for App Stores

  18. Extracting features from description of apps A feature to be a property, captured by a set of words in the app description and shared by a set of apps.

  19. Extracting features from description of apps A feature to be a property, captured by a set of words in the app description and shared by a set of apps. e.g. Finance - setup, bank, accounts - calculate, monthly, expenses - e-mail, alerts, stock - create, watch, lists - financial, business, news

  20. Extracting features from description of apps A feature to be a property, captured by a set of words in the app description and shared by a set of apps. e.g. Finance e.g. Travel - setup, bank, accounts - free,wifi - calculate, monthly, expenses - wifi, hotspot, near - e-mail, alerts, stock - download, offline, use - create, watch, lists - restaurants, plotted, map - financial, business, news - bus, service

  21. MSR for App Stores

  22. App Features MSR for App Stores

  23. App Features MSR for App Stores

  24. E.g cost for features MSR for App Stores

  25. E.g cost for features C ( )+C( )+C( ) 3 MSR for App Stores

  26. E.g cost for features C ( )+C( )+C( ) 3 MSR for App Stores

  27. Do higher rated apps get more downloads? MSR for App Stores

  28. Do higher rated apps get more downloads? Apps Features Spearman rank 0.79 0.89 correlations (Ratings, Rank of Downloads) MSR for App Stores

  29. What’s the chance of producing a similar feature correlation purely at random ? MSR for App Stores

  30. What’s the chance of producing a similar feature correlation purely at random ? MSR for App Stores

  31. What’s the chance of producing a similar feature correlation purely at random ? MSR for App Stores

  32. How price sensitive are customers? MSR for App Stores

  33. How price sensitive are customers? Apps Features Spearman rank 0.12 -0.09 correlations (Price, Rank of Downloads) MSR for App Stores

  34. Which feature shall I include in a travel app? MSR for App Stores

  35. Current work Predictive Models for App prices

  36. Conclusion App Store: a new form of software repository Rich source of information Customer Technical Business http://www.cs.ucl.ac.uk/staff/Y.Jia/projects/app_store_mining MSR for App Stores

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