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Best Dissertation Symposium: Reducing user-perceived latency in mobile applications via prefetching and caching

Best Dissertation Symposium: Reducing user-perceived latency in mobile applications via prefetching and caching

Slides for my PhD dissertation "Reducing user-perceived latency in mobile applications via prefetching and caching", presented at the Best Dissertation Symposium 2021 at the University of Southern California.
Presentation on YouTube: https://youtu.be/a5oTwih9rkE

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Yixue Zhao

May 13, 2021
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Transcript

  1. Reducing User-Perceived Latency in Mobile Applications via Prefetching and Caching

    Yixue Zhao Advisor: Nenad Medvidović Computing Innovation Fellow (CIFellow) University of Massachusetts Amherst
  2. None
  3. None
  4. Latency!

  5. Latency Problem Angry Users Sales Loss 5

  6. Main Cause: Network Transfer Network round trip Mobile App Remote

    Server Main cause of user-perceived latency is network transfer since mobile apps spend most time fetching data from remote servers. [Ravindranath et al. OSDI’12] 6
  7. Effective Solution! Problem: Annoying loading wheel L Solution: Prefetching and

    Caching 7
  8. Prefetching and Caching local cache on the phone immediate response!

    8
  9. Prefetching and Caching 9 ? But how?

  10. 10 Literature Study Techniques Testing

  11. 1. Two categories Literature Study Techniques Testing 11

  12. Two Categories q Content-based q No existing solution q Call

    for novel idea q History-based q Applicable existing solution q Adapt to mobile domain 12
  13. q Content-based q No existing solution q Call for novel

    idea q History-based q Applicable existing solution q Adapt to mobile domain 13 Techniques Two Categories
  14. 14 2. Is it a good idea? Literature Study Techniques

    Testing
  15. 15 Literature Study Techniques Testing 2. Is it a good

    idea?
  16. 16 3a. Content-based (first work) Literature Study Techniques Testing

  17. Content-based: PALOMA Key Insights q App’s code has all we

    need q “User think time” provides opportunities 17
  18. PALOMA at a High Level Code Analysis App Rewriting Optimized

    App 18
  19. PALOMA at a High Level 19 Automatic No other information

    required 99% latency reduction! Code Analysis App Rewriting Optimized App
  20. 20 Literature Study Techniques Testing 3b. History-based (practical solution)

  21. History-based: HiPHarness 21 Existing Solutions HiPHarness q Large prediction models

    q Big cost q Privacy issues
  22. History-based: HiPHarness 22 Existing Solutions HiPHarness q Large prediction models

    q Big cost q Privacy issues q Small prediction models! q Good training data q Enough training data
  23. History-based: HiPHarness 23 Existing Solutions HiPHarness q Large prediction models

    q Big cost q Privacy issues q Small prediction models! q Good training data q Enough training data 94% smaller!
  24. HiPHarness Dataset q 10,000+ mobile users q 15+ million network

    requests q 7+ million prediction models 24
  25. q Small prediction models work great! q Win-win (reduce size

    AND improve accuracy) q Challenged prior conclusion q Re-opened this area HiPHarness Takeaways 25 Less is More!
  26. 26 Literature Study Techniques Testing 4. Which is better?

  27. Challenges in Testing q Testing prefetching and caching techniques is

    very expensive q Require real-user traces (i.e., “usage-based test”) q hire participants q obtain permission q provide guidelines q provide compensation q … 27
  28. Challenges in Testing q Testing prefetching and caching techniques is

    very expensive q Require real-user traces (i.e., “usage-based test”) q hire participants q obtain permission q provide guidelines q provide compensation q … 28 I need this!
  29. Usage-based Test Background q Emerging research area in Software Testing

    (since 2018) q State-of-the-art research: test-reuse techniques 29
  30. FrUITeR at a High Level q Goal: find out who’s

    better q Reproduce existing techniques q Establish standard pipeline q Fair comparison in the same way A Framework for Evaluating UI Test Reuse 30
  31. Challenges in Practice Discuss with authors 31 Study implementation Modify

    implementation Establish benchmark Construct ground truths
  32. Reproducibility Crisis 32 Common Theme q “It’s hard to (re)use

    other research tools” q “They don’t have documentation” q “It’s hard to run a research tool on my own apps” q …
  33. 33 FrUITeR’s Open Science Contribution FrUITeR’s Website: https://felicitia.github.io/FrUITeR/

  34. v Prefetching & caching is good idea J encouraged more

    techniques Recap Dissertation Contributions 34
  35. v Prefetching & caching is good idea J encouraged more

    techniques v First content-based (PALOMA) inspired follow-up work Recap Dissertation Contributions 35
  36. v Prefetching & caching is good idea J encouraged more

    techniques v First content-based (PALOMA) inspired follow-up work v Make history-based practical (HiPHarness) challenged prior conclusion & re-opened this area Recap Dissertation Contributions 36
  37. v Prefetching & caching is good idea J encouraged more

    techniques v First content-based (PALOMA) inspired follow-up work v Make history-based practical (HiPHarness) challenged prior conclusion & re-opened this area v Test which is better (FrUITeR) set standards for a fair playground Recap Dissertation Contributions 37
  38. 4. Which is better? (FrUITeR) Dissertation & Beyond Mobile-App Performance

    38 Software Testing Open Science
  39. Dissertation Publications v Literature Review & Empirical Study [ASE 2018]

    v Prefetching & Caching Techniques [MOBILESoft 2017 SRC ICSE 2018, MOBILESoft 2021] v Software Testing [ESEC/FSE 2020] v Open Science [MOBILESoft 2019 Visions, ICSE 2019 Doctoral Symposium] 39
  40. Dissertation Publications v Literature Review & Empirical Study [ASE 2018]

    v Prefetching & Caching Techniques [MOBILESoft 2017 SRC ICSE 2018, MOBILESoft 2021] v Software Testing [ESEC/FSE 2020] v Open Science [MOBILESoft 2019 Visions, ICSE 2019 Doctoral Symposium] 40 https://tinyurl.com/yixuedissertation https://tinyurl.com/yixuetalks
  41. Thank you! 41