Mobile App Discovery through Conceptual Models



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Transcription:

Mobile App Discovery through Conceptual Models Jasmin Brakmic, BSc Supervisor: Prof. Dr. Dimitris Karagiannis Research Group Knowledge Engineering University of Vienna, 24.01.2013

Agenda 1. Motivation 2. Objectives 3. Related Work 4. Design and Implementation Framework 5. Master thesis roadmap

Motivation Growing trend in the development of mobile applications. Google Play Store & ios App Store -> over 600.000 mobile apps. Nokia Ovi Store & Microsoft Store -> over 120.000 mobile apps. Mobile apps currently mainly developed from scratch-> time consuming and resource intensive development process. Implementation specific information cannot be accessed by developers and often does not fit the requirements for functionality because of inadequate search mechanisms.

Objectives Design modelling support for: description of mobile app capabilities app code selection and reuse Implement: an appdiscoveryweb service as proof-of-concept

Related Work Technological-oriented Regarding app implementation: Guidelines for various platforms (Android, ios, Windows Phone, etc.) Regarding mobile app functionality description: UIML (User Interface Markup Language) UsiXML (USer Interface extensible Markup Language) XIML (extensible Interface Markup Language) Regarding web service description and discovery: SOA technologies: UDDI, WSDL

Related Work Theoretical-oriented Regarding mobile app discovery focused on deployed apps: B. Yan and C. Guanling. "AppJoy: personalized mobile application discovery." In Proceedings of the 9th international conference on Mobile systems, applications, and services, pp. 113-126. ACM, 2011. A. Karatzoglou, L. Baltrunas, K. Church and M. Böhmer. "Climbing the App Wall: Enabling Mobile App Discovery through Context-Aware Recommendations." (2012). Regarding mobile app design: J. Ziegler, M. Graube, J. Pfeffer, and L. Urbas, Beyond App-Chaining - Mobile App Orchestration for Efficient Model Driven Software Generation, Proc. of the 17th IEEE International Conference on Emerging Technologies and Factory Automation ETFA 2012. Related to modelling and modelling methods: D. Karagiannis and H. Kühn, Metamodelling Platforms, in EC-WEB 02: Proceedings of the Third International Conference on E-Commerce and, London, UK, 2002. Regarding semantic description of web services: M. Paolucci, T. Kawamura, T. Payne and K. Sycara. "Semantic matching of web services capabilities." The Semantic Web ISWC 2002 (2002): 333-347.

FRAMEWORK

Framework inspired by the Publish-Bind Model for Web Services UDDI (Service Directory) Find service Register service Service consumer Uses service Service provider App directory Model-based search for app code Registers app code App developer (as consumer) Reuses/adapts app App developer (as provider)

Domain expert Proposed procedure and architecture Provider Identifies domain is described by Assuemed steps Supported steps To be implemented/defined Reused from ComVantage Consumer Identifies domain User Interaction specific models Creates model and app Process model App models Creates models Repository Web logic Web service interface Registers model and code Stores model and code Search algorithm used for request Concept-based structure Queries Reusable/Adaptable code Uploads models as queries Receives requested apps

View details Areas supported and described by App Models App Capability Preconditions Effects App Choreography (user interaction) App Orchestration (interapp interactions) Task overview Provide Pressure Task 1 Task 2 Task 3 Task 4 Ok App Information Resources App1 ~~~~~~ ~~~~~~ ~~~ ~~~~~~ ~~~~~~ ~~~ Will be used from the ComVantage Project.

Queries As an input for queries the Process model and App models will be used. Query examples based on: Capabilities: Find me an app which provides authentication and book buying capabilities. Information resources: Find me an app which produces as output a bill. App structure: Provide me with an app which takes as input an username and password and sends the information to a server.

Search Algorithm The search algorithm will consider and extract the information stored in the conceptual models and try to find implementation specific information from the repository. Because of the diversity of the conceptual models for each model different comparison approaches will be used. Comparison will be based on: Capabilities and Information, Mobile App structure, Mobile App Orchestrations (in progress).

Proposed Comparison Approaches for Conceptual Models Comparison based on Capabilities and Information resources ->Jaccard similarity coefficient. Comparison based on two mobile app structure-> Pearson Correlation Coefficient., 1,1

Mobile App Repository Is aimed to hold implementation and conceptual specific information about mobile apps. The repository should not be restricted to a certain implementation type (e.g. Android). Challenges for structure and interface: Semantic enrichment of mobile app search? Storage structure? Mobile app queries? <?xml version="1.0" encoding="utf-8"?> <LinearLayout xmlns:android="http://schemas.android.com/ apk/res/android" android:layout_width="fill_parent" android:layout_height="fill_parent" android:orientation="vertical" > <TextView android:id="@+id/text" android:layout_width="wrap_content" android:layout_height="wrap_content" android:text="hello, I am a TextView" /> <Button android:id="@+id/button" android:layout_width="wrap_content" android:layout_height="wrap_content" android:text="hello, I am a Button" /> </LinearLayout> http://developer.android.com/guide/topics/ui/index.html

Search algorithm expected results The search algorithm should not only perform querying on one mobile application, instead it should consider the best fitting combination of mobile application components of different mobile applications. The user should be provided with a possibility to define the number of best results, which should be returned. Example: Mobile repository Required mobile app

Roadmap

Thank You For Your Attention! Jasmin Brakmic, BSc University of Vienna Faculty of Computer Science Research Group Knowledge Engineering Währinger Straße 29 A-1090 Wien jasmin.brakmic@univie.ac.at