Automated Software Testing to Discover Energy Inefficiencies in Mobile Apps

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1 Automated Software Testing to Discover Energy Inefficiencies in Mobile Apps Sudipta Chattopadhyay Linköping University, Sweden Joint work with Abhijeet Banerjee, Lee Kee Chong and Abhik Roychoudhury National University of Singapore

Linköping University, Sweden Joint work with Abhijeet

2 Context Developer Write energy-efficient! software Programming abstractions Tools and techniques Desktops, handheld devices etc. 2

3 Overview Tools and techniques to write energy-efficient software Energy-aware! Software Testing Energy-hungry! Code Patterns Energy-aware! Coding Guidelines Desktop machines, handheld devices etc. 3

4 Overview Tools and techniques to write energy-efficient software Energy-aware! Software Testing Energy-hungry! Code Patterns Energy-aware! Coding Guidelines Desktop machines, handheld devices etc. Android Devices 4

5 Smartphone Market Smartphone Sales Mobile App Testing Market Size $2.30 Billion Dollars $0.70 $0.80 $ Data obtained from IDC, Gartner and ABI Research

6 Energy Inefficiency How do we quantify energy inefficiency? High energy consumption, what is high?! High energy consumption High utilization of hardware components Low utilization of hardware components Ratio Energy/Utilization

! High energy consumption High utilization of hardware

7 Energy Inefficiency Cause/Source Hardware components Resource leak Suboptimal resource binding Sleep state transition Wakelock bug Tail Energy hotspot Background Service Vacuous background service Expensive background service Defective Functionality Immortality bug Loop energy hotspot

Energy hotspot Background Service Vacuous background service Expensive

8 Energy Inefficiency Wasted Energy Resource acquired Resource first used Suboptimal resource binding Wasted Energy Service started Never used Vacuous background service

9 A Broader Categorization Cause/Source Energy Bugs Energy Hotspots Hardware components Resource leak Suboptimal resource binding Sleep state transition Wakelock bug Tail Energy hotspot Background Service Vacuous background service Expensive background service Defective Functionality Immortality bug Loop energy hotspot Device does! not return to idle High energy consumption! + low utilization

Background Service Vacuous background service Expensive background service Defective Functionality

10 Measurement Yokogawa Digital Power Meter LG Optimus smartphone Our framework

11 Measurement Measuring Energy/Utilization ratio for an application Energy/Utilization Time App is not executing (PRE) App is executing events (EXC) Recovery (REC) Idle (POST)

12 Energy Inefficiency Comparable Energy/Utilization Time App is not executing (PRE) App is executing events (EXC) Recovery (REC) Idle (POST)

13 Energy Inefficiency Comparable Energy/Utilization Time Not Comparable Energy/Utilization Energy Bugs App is not executing (PRE) Time App is executing events (EXC) Recovery (REC) Idle (POST)

14 Energy Inefficiency Energy/Utilization Normal behavior Time App is not executing (PRE) App is executing events (EXC) Recovery (REC) Idle (POST)

15 Energy Inefficiency Energy/Utilization Normal behavior Time Energy/Utilization Energy Hotspots App is not executing (PRE) Abnormal! (high energy! low utilization) Time App is executing events (EXC) Recovery (REC) Idle (POST)

16 Test Generation Our framework Detecting Energy Inefficiency Guiding to execute energy-inefficient scenarios

17 Test Generation Our framework Detecting Energy Inefficiency Guiding to execute energy-inefficient scenarios

18 Measurement Yokogawa Digital Power Meter Record Energy Trace LG Optimus smartphone Send events Record Utilization

19 Measurement Yokogawa Digital Power Meter Record Energy Trace LG Optimus smartphone Global! clock Send events Record Utilization

20 Utilization Energy consumption of different components is not even (GPS < CPU) 100% CPU does not consume same energy as GPS being on

21 Detecting Energy Bugs Comparable Energy/Utilization Time Not Comparable Energy/Utilization Statistical! dis-similarity! between! PRE and POST App is not executing (PRE) Time App is executing events (EXC) Recovery (REC) Idle (POST)

22 Detecting Energy Hotspots Energy/Utilization Normal behavior Time Energy/Utilization Detecting! discords in! time-series! data App is not executing (PRE) Abnormal! (high energy! low utilization) Time App is executing events (EXC) Recovery (REC) Idle (POST)

23 Test Generation Our framework Detecting Energy Inefficiency Guiding to execute energy-inefficient scenarios

24 Guided Exploration Energy-inefficient execution Which fragments are energy-inefficient? What is an appropriate coverage metric?

25 A Broader Categorization Cause/Source Energy Bugs Energy Hotspots Hardware components Resource leak Suboptimal resource binding Sleep state transition Wakelock bug Tail Energy hotspot Background Service Vacuous background service Expensive background service Defective Functionality Immortality bug Loop energy hotspot Invoked via System Calls

26 Test Generation Our framework Detecting Energy Inefficiency Guiding to execute energy-inefficient scenarios Android App + System call pool Event flow graph To smartphone Event trace Guided exploration Event trace database

27 Test Generation Android App + System call pool Event flow graph To smartphone Event trace Guided exploration Event trace database T1 > T2 s1 s1 An ordering between trace T1 and T2 Buggy trace s1! T1 > T2! s1 s5 Executed trace s1 T1 < T2 s1 s5 s2 s2 s2 s2 s6 s2 s2 s6 s3 More system calls s3 Similarity with buggy trace s4 s3 Covering more system calls

28 Evaluation Travel/Transportation Lifestyle/Health Books/News Productivity Photography/Media Entertainment Puzzle Tools Category of Android Apps Evaluated

29 Summary of Evaluation App Feasible! traces Energy Bugs Energy! Hotspots Type Reported! before Aripuca 502 Yes No Vacuous background service No Montreal Transit Sensor Test 64 No Yes Suboptimal resource binding and more No 2800 Yes No Immortality Bug No 760 KFMB AM 26 Yes Yes Vacuous background service, suboptimal resource binding No All Results are in the paper (10 energy bugs and 3 energy hotspots found out of 30 tested apps)

30 Summary of Evaluation App System call! Code! Lines of Code Aagtl coverage 100 coverage Android Battery Dog Aripuca Kitchen Timer Montreal Transit NPR News OmniDroid Pedometer Vanilla Music Player To cover all system calls, exploring only a small part of the program suffices A substantial portion of the code is used for provide user feedback, compatibility over different OS

31 Case Studies Aripuca (Energy Bug) Reason: Vacuous Background Service Fix: serviceconnection.getservice().stoplocationupdates(); serviceconnection.getservice().stopsensorupdates();

32 Case Studies Aripuca (Energy Bug) Reason: Vacuous Background Service

33 Case Studies Montreal Transit (Energy hotspot for <5 sec) Loading Ads Main Thread Location service Location service (for loading ads) User exits GPS released

34 Case Studies Montreal Transit (Energy hotspot for <5 sec) Loading Ads Main Thread Location service Location service (for loading ads) User exits Loading Ads by Asynchronous thread GPS released Main Thread Location service Share location for loading ads User exits GPS released

35 Case Studies Montreal Transit (Energy hotspot for <5 sec) Montreal Transit (After fixing)

36 Summary Categorization of energy inefficiency Energy bugs Energy hotspots A guided exploration of event traces Targeting system call coverage Evaluation with Android apps Energy bugs and hotspots exist in several Android apps

37 Open Problems Event Flow Graph may require intelligent inputs Games Confirmation of bugs/hotspots require repeated execution Debugging and optimization is manual

Detecting Energy Bugs and Hotspots in Mobile Apps

Detecting Energy Bugs and Hotspots in Mobile Apps Abhijeet Banerjee 1 Lee Kee Chong 1 Sudipta Chattopadhyay 2 Abhik Roychoudhury 1 1 National University of Singapore, Singapore 2 Linköping University,