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Navigation-aware and Personalized
Prefetching of Network Requests in
Android Apps
Ivano Malavolta, Vrije Universiteit Amsterdam
Francesco Nocera, Polytechnic University of Bari
Patricia Lago, Vrije Universiteit Amsterdam
Marina Mongiello, Polytechnic University of Bari
Network prefetching
2
▣ Most apps interact with backend services
via HTTP-based RESTful interactions
▣ à ~800 ms of latency before showing the
actual data for each request
▣ PREFETCHING = loading data before it is
required to decrease the user-perceived
waiting time
Backend
https://api.sn.com/media/ □ / □
https://api.sn.com/media/ □ / □
https://api.sn.com/group/ □
https://api.sn.com/ □ /info
https://api.sn.com/ □ /info
https://api.sn.com/ /friends
Intuition
3
Home
Profile
Friends
24
ivanouId
Extras
Group
Page
Media
3
10 15
Backend
AdditionalInfo
5
2
ivano
▣ Extended Navigation Graph
(ENG)
userId
intent
intent
intent
intent
intent
intent
NAPPA
4
Navigation-
Aware
Personalized
Prefetching of
Android apps
Main characteristics
□ Android activities as black boxes
■ Lightweight
■ High level of abstraction
□ Prefetching algorithm-independent
□ Adapts to each user navigation patterns
□ The ENG is built at run-time
■ Reflection
■ Multi-threading
■ ...
https://api.sn.com/media/ □ / □
https://api.sn.com/media/ □ / □
https://api.sn.com/group/ □
https://api.sn.com/ □ /info
https://api.sn.com/ □ /info
https://api.sn.com/ /friends
Home
Profile
Friends
24
au53defguId
Extras
Group
Page
Media
3
10 15
Backend
AdditionalInfo
5
2
uId
NAPPA at development time
5
Original
app
Extract
activities
Inject navigation
probes
Inject extra
probes
ENG
instrumentation
Instantiate
network
interceptor
NAPPA at run-time
6
Prefetching-enabled app
Instrumented
code
Extras
monitor
Prefetcher
Backend
Network
interceptor
0.8
0.10.1
0.5
0.5
URL map
ENG
triggers
populates
fetches
fetches
analyses
Navigation
monitor
fetches
update
What’s next?
7
▣ Empirical evaluation
▣ Different prefetching algorithms
□ Greedy algorithm à ENG as a Markov chain?
▣ Detecting dynamic URL fragments beyond intent extras
□ URL fragments emerging from user input, local DBs, shared preferences,
etc.
□ Dynamic taint analysis?
▣ Extend the current prototype
□ https://github.com/S2-group/NAPPA
DATASET OF REAL
USAGE SCENARIOS
NEEDED!

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Navigation-aware and Personalized Prefetching of Network Requests in Android Apps [ICSE 2019 NIER track]

  • 1. Navigation-aware and Personalized Prefetching of Network Requests in Android Apps Ivano Malavolta, Vrije Universiteit Amsterdam Francesco Nocera, Polytechnic University of Bari Patricia Lago, Vrije Universiteit Amsterdam Marina Mongiello, Polytechnic University of Bari
  • 2. Network prefetching 2 ▣ Most apps interact with backend services via HTTP-based RESTful interactions ▣ à ~800 ms of latency before showing the actual data for each request ▣ PREFETCHING = loading data before it is required to decrease the user-perceived waiting time Backend
  • 3. https://api.sn.com/media/ □ / □ https://api.sn.com/media/ □ / □ https://api.sn.com/group/ □ https://api.sn.com/ □ /info https://api.sn.com/ □ /info https://api.sn.com/ /friends Intuition 3 Home Profile Friends 24 ivanouId Extras Group Page Media 3 10 15 Backend AdditionalInfo 5 2 ivano ▣ Extended Navigation Graph (ENG) userId intent intent intent intent intent intent
  • 4. NAPPA 4 Navigation- Aware Personalized Prefetching of Android apps Main characteristics □ Android activities as black boxes ■ Lightweight ■ High level of abstraction □ Prefetching algorithm-independent □ Adapts to each user navigation patterns □ The ENG is built at run-time ■ Reflection ■ Multi-threading ■ ... https://api.sn.com/media/ □ / □ https://api.sn.com/media/ □ / □ https://api.sn.com/group/ □ https://api.sn.com/ □ /info https://api.sn.com/ □ /info https://api.sn.com/ /friends Home Profile Friends 24 au53defguId Extras Group Page Media 3 10 15 Backend AdditionalInfo 5 2 uId
  • 5. NAPPA at development time 5 Original app Extract activities Inject navigation probes Inject extra probes ENG instrumentation Instantiate network interceptor
  • 6. NAPPA at run-time 6 Prefetching-enabled app Instrumented code Extras monitor Prefetcher Backend Network interceptor 0.8 0.10.1 0.5 0.5 URL map ENG triggers populates fetches fetches analyses Navigation monitor fetches update
  • 7. What’s next? 7 ▣ Empirical evaluation ▣ Different prefetching algorithms □ Greedy algorithm à ENG as a Markov chain? ▣ Detecting dynamic URL fragments beyond intent extras □ URL fragments emerging from user input, local DBs, shared preferences, etc. □ Dynamic taint analysis? ▣ Extend the current prototype □ https://github.com/S2-group/NAPPA DATASET OF REAL USAGE SCENARIOS NEEDED!