In recent years, technological growth has been exponential in relation to mobile devices (such as embedded sensors as GPS or accelerometer) that has allowed developing context-aware mobile applications for the market. This growth generates a new challenge about how to support the creation of this kind of application in order to adapt them to the user’s current demand. There are at present several approaches that could be used to create context-aware mobile applications, but these approaches are not designed to support variability in the kind of generated applications.Our aim is to propose a building tool that allows generating a wide variety of applications. Our tool has been designed from scratch considering a taxonomy of variability concepts (relevance, combination, precision and accuracy’s margins, configuration type, and execution type) which help to identify the potential variability points to obtain more flexible building approaches. Estevan Gomez, Universidad de las Fuerzas Armadas - ESPE Estevan R. Gómez-Torres, PhD (c) Universidad Nacional de la Plata Argentina, Master in Systems Management and Systems Engineering from Universidad de las Fuerzas Armadas 'ESPE' in Quito-Ecuador. His field of work and research include lines such as: Big Data, Internet of Things, Project Management, Development of mobile applications in contexts, Artificial Intelligence, Data Analytics, Machine Learning, Smart Cities.

1. Developing a
New Tool of DSL
for Context-
aware Mobile
Applications

2. Agenda
 Background related to Context-Aware Mobile Applications
 Taxonomy of factors that should be considered by context-
aware mobile application building approaches
 Construction of DSL with Obeo Designer
 Discussion
 Conclusions y Future Works

3. ContextAware
➢ Who?
➢ What?
➢ Where?
➢ When?

4. Background related to Context-Aware Mobile Applications
 Technological Advances
❑ Varied range of mobile applications
❑ A lot of sensed data

5. Background related to Context-Aware Mobile Applications
 Technological Advances
❑ Varied range of mobile applications
❑ A lot of sensed data
 Explored by different areas of
Computer Science
❑ Artificial Intelligence
❑ Home Automation
❑ …

6. Background related to Context-Aware Mobile Applications
 Technological Advances
❑ Varied range of mobile applications
❑ A lot of sensed data
 Explored by different areas of
Computer Science
❑ Artificial Intelligence
❑ Home Automation
❑ …
 Variety of Perspectives
❑ Currently no unified solution

7. Background related to Context-Aware Mobile Applications
 Indoor Location Systems
❑ Varied of indoor location sensing
mechanisms
❑ WLAN
❑ BLE
❑ …
❑ Currently no unified solution

8. Background related to Context-Aware Mobile Applications
Development of context-aware mobile applications
is a complex task

9. Background related to Context-Aware Mobile Applications
Development of context-aware mobile applications
is a complex task
Building approaches to speed up this task
Non-expert approaches
(App Inventor)

10. Background related to Context-Aware Mobile Applications
 App Inventor
❑ Create Android applications → without
having any technical knowledge
❑ Only GPS as a location sensing
mechanism, allowing:
▪ precision and accuracy
configuration
❑ Create only applications for outdoor
spaces
❑ Not possible → combine accelerometer
sensor with orientation sensor
❑ Focuses only on some contexts of the
device and user’s location

11. Background related to Context-Aware Mobile Applications
Development of context-aware mobile applications
is a complex task
Building approaches to speed up this task
Non-expert approaches
(App Inventor)
Expert approaches
(WebRatio Mobile)

12. Background related to Context-Aware Mobile Applications
 WebRatio Mobile
❑ For expert users → knowledge of databases
and hypermedia design
▪ Generated PhoneGap applications
(Android and iOS platforms)
❑ Only GPS as a location sensing mechanism,
allowing:
▪ precision and accuracy
configuration
❑ Create only applications for outdoor
spaces
❑ Defining contexts related to Device,
Network Connectivity and Position

13. Background related to Context-Aware Mobile Applications
Non-expert approaches
(App Inventor)
Expert approaches
(WebRatio Mobile)
Derived applications are limited
(e.g. address certain specific aspects, only GPS)
restrictions → related to the available APIs

14. Background related to Context-Aware Mobile Applications
¿How to manage a wide range of generated
applications for building approaches?
Taxonomy of factors proposed

15. Taxonomy of factors proposed

16. Construction of DSL

17. What are Domain Specific Languages?
• Domain Specific Languages are
languages created to support a
particular set of tasks, as they
are performed in a specific domain.
• Typical programming languages,they
are tools good enough to create all
sort of programs, but not really specific
to anything.
• They are like hammers: good enough
for many tasks, if you have the
patience and ability to adapt them,
but in most cases you would be better
off using a more specific tool.

18. Considerations for our DSL.

19. Ecore meta-model with the basic context-aware and
variability concepts

20. LAUNCH DE OBEO RUN TIME

21. Intermediate models associated to visual DSL of our tool.

23. Creation of several layers of
Representation in View Point

24. DEFINITION OF DSL-CASE1: AWARE OBJECT AUTOMOVIL

25. Outdoor positioning

26. DEFINITION OF DSL-CASE2: CLIMATE( outdoor)

27. indoor positioning

28. DEFINITION OF DSL-CASE2: Meeting( Indoor Positioning)

29. Testing the Tool

30. View of all the Cases Generated

31. Discussion
 The Taxonomy factors are developed depending on who will use: users ( experts or non experts)
 Used by expert users
❑ Factors of relevance, combination, precision and accuracy
 Understood by non-expert users
❑ Categorization of context depending on how it is presented from the approach
 GPS APIs
❑ Allowing approaches generate applications for outdoor spaces
 Flexibility provided by building approaches
❑ What users/developers will be able to generate
 Taxonomy of factors proposed
❑ Could contribute to improving the flexibility of approaches

32. Conclusions y Future Works
 Our DSL is already constructed
❑ We have testesd it for
❑ Indoor context-aware mobile applications
❑ Outdoor context-aware mobile applications
 We will be designing the process with Acceleo for
❑ Generating Android context-aware mobile applications
❑ We will be generating a Mobile Application Test
❑ We will explore
 How to enrich our taxonomy with, for example, complementary aspects of context-
aware mobile applications

34. Contacts
Estevan R. Gómez-Torres,
Cecilia Challiol, Silvia E. Gordillo
ergomez@espe.edu.ec,
{ceciliac,gordillo}@lifia.info.unlp.e
du.ar

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