Robot Aided Test Automation Collecting and utilizing user data

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1 Robot Aided Test Automation Collecting and utilizing user data Testiautomaatiopäivä 2014 Jussi Liikka, Arttu Lämsä, Miska Seppänen VTT Technical Research Centre of Finland

2 Click Outline to edit Master title style 1. Introduction Click to edit Master text styles 2. Architecture Second level overview 3. Client and the collected data 4. Preprocessing the data 5. Generating the Markov Model 6. Robot controlling 7. More detailed UI usage tracking 8. Data collection overview 9. Examples 10. Future work & Conclusions 05/06/2014 2

3 Click Introduction to edit Master title style When testing extensive software components, such as mobile Click to edit Master text styles platforms, number of test cases is high Second level How to prioritize testing? Real-life user data can be collected and used to determine the most used elements and patterns of the software platform A model provides probabilities of transitions between user interface elements How to realistically test current consumption and device aging? By generating usage patterns from the collected user data and by using it in robot based testing via user interface 05/06/2014 3

4 Click Introduction to edit Master (cont.) title style A mobile client, operating completely Click transparent to edit to Master the user, text collects styles user data Statistical Second model level of the information gathered from multiple devices Robot controlling utilizes the collected user data Image: 05/06/2014 4

5 Click Architecture to edit Master overview title style 1. Client devices collect data and send it to the server Click to edit Master text styles Second level 2. Data is preprocessed (periodically) 3. MarkovAnalyzer reads preprocessed data and generates Markov models from the user data 4. Markov models can be used to control automated testing robots 05/06/2014 5

6 Click Client to and edit the Master collected title style data An Android client collects user data Click The to client edit Master is transparent text styles to the user The Second client collects level the following data Foreground activity name (timestamps tracked when an activity is changed) Touch events (coordinate and timestamp) Hard button events Screenshots (partial and whole screen) Icons of the used applications The collected data is stored into the internal memory of the mobile device The data is then converted into JSON format and transferred to a server along with the screenshots once per day 05/06/2014 6

7 Click Preprocessing to edit Master the data title style The Click server to edit receives Master the text data styles and stores the raw JSON data into a temporary database Second level table A preprocessing Fourth utility level processes the data and stores it into multiple database tables Tables for Android activity changes, screen touch events, etc. The preprocessing utility works as a batch process that is executed e.g. once per day 05/06/2014 7

8 Click Generating to edit the Master Markov title Model style MarkovAnalyzer utility reads the Click data from to edit the Master database text and styles generates Second a level Markov model The model Third contains level the Android activities, transition Fourth level probabilities between them, touch paths (coordinate sequences leading from one activity to another), icon of the activity and filename of the activity screenshot The model can be created from single user s data or by combining data from multiple users Image from: (Creative Commons Attribution-Share Alike 3.0 Unported license, author Joxemai4) 05/06/2014 8

9 Click Generating to edit the Master Markov title model style (cont.) <MarkovModel> <GuiState> <ID>0</ID> <ActivityClassName>eu.chainfire.supersu.PromptActivity</ActivityClassName> Click <TimesVisited>9</TimesVisited> to edit Master text styles <Transitions> <Transition> Second level <ID>1</ID>. <Probability>1</Probability> <Triggers> <Trigger> <Path> <Coordinate> <X>390</X> <Y>1256</Y> <Delay>1000</Delay> <Orientation>1</Orientation> </Coordinate></Path> </Trigger> <Trigger> <Path> <Coordinate>... P1 P11 P12 05/06/2014 9

10 Click Robot to controlling edit Master title style Open Source Modelling Objects (OSMO) is a set of tools and Click to edit Master text styles libraries for model-based testing of systems and software Second level Robot controlling Third level scripts can be generated from Markov models by using OSMO or Markov2Robot utility The generated scripts contain touch coordinates, delays between them and the icon file names 05/06/

11 Click More to detailed edit Master UI usage title tracking style Click to edit Master text styles Second level Client software takes a small partial screenshot from users last touched position of the screen. Partial screenshot image is compared to collection of images available in a test model. A predefined test model contains information about application views and transformations between them. Test sequence generator is now able to imitate the real user according to the probabilities calculated from recorded data. 05/06/

12 Click Data collection to edit Master overview title style Click Five users to edit over Master period text of styles 6 months ~3.2 Second million level touch event samples 150k application events 498 different Android activities 05/06/

13 Click Example to edit Master analysis title of style the collected data Robot control Click Robot to controlling edit Master LG text Google styles Nexus Second 4 based level on the collected user data The robot is Fourth hosted level by Optofidelity in Tampere 05/06/2014 OptoFidelity. OptoFidelity HSUF One Finger Touch and Test System. 13

14 Click Example to edit Master analysis title of style the collected data Touch events Click to edit Master text styles Second level Heatmap was generated from all of the collected touch events from all users Most used parts of the screen shown in light colors 05/06/

15 Example analysis of the collected data Click to edit Master Partial title image style analysis Background image All touch positions Overlay Click to edit Master text styles Second level 05/06/

16 Click Future to work edit Master title style Dynamic content recognition Click to edit Master text styles Perceptual Second level computing Suitable metrics for behavioral testing 05/06/

17 Click Conclusion to edit Master title style Click How to to edit prioritize Master testing? text styles Our approach was the utilisation of user data Second level Collect real-life user data of touch screen mobile devices Model can be constructed from collected user data Model can be utilized for example test case prioritization or user interface navigation analysis Contact information More information about VTT s test automation research 05/06/

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