Raian ali fabiano dalpiaz paolo giorgini
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Location-based Software Modeling and Analysis: Tropos-based Approach. Raian Ali, Fabiano Dalpiaz , Paolo Giorgini. 2. 2. Talk outline. Limits of existing modeling techniques Location-based Software Modeling challenges Features to support Tropos and location-based SW

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Raian ali fabiano dalpiaz paolo giorgini

Location-based Software Modeling and Analysis: Tropos-based Approach

Raian Ali, Fabiano Dalpiaz, Paolo Giorgini


Talk outline

2

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R. Ali, F. Dalpiaz, P. Giorgini

Talk outline

  • Limits of existing modeling techniques

  • Location-based Software

    • Modeling challenges

    • Features to support

  • Tropos and location-based SW

    • Advantages and drawbacks of Tropos

    • Location-based Tropos

    • Location-based Tropos process

    • Location-based analysis

  • Conclusions


Research question

Research question

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  • The concept of location is becoming more and more important (e.g. Ubiquitous computing, AmI)

  • Location-based software is characterized by its ability to

    • Reason about the surrounding location

    • Adapt autonomously its behavior to be location compliant

What and How to model and analyzelocation-based SW?


Limits of existing models context models

Limits of existing models: context models

Several context models have been proposed

Ontology-based [Yau et al., 2006] [Wang et al., 2004]

Object-based [Henricksen et al., 2004]

They don’t specify the relation between context and its use

Why is context needed?

Which is the relevant part of context?

Context awareness is mainly focused on the software domain, not on the problem domain.

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Limits of existing models variability models

Limits of existing models: variability models

SW product line engineering creates systematically a diversity of similar products at low costs, in short time, and with high quality [Pohl et al., 2005].

To model location-based software we need:

Autonomous selection between features

Higher level of abstraction that justifies the features

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Feature models [Kang et al., 1998]


Location based sw modeling challenges

Location modeling constructs

What is the conceptual framework?

Location relevancy

What should be modeled?

Location rules

Constraints of the specific location

Location-based behavior

Different behaviors are enabled/disabled depending on the current location

Location-based SW: modeling challenges


Location based sw modeling challenges1

Hierarchical behaviors construction

Avoid “one location, one behavior” cases

Location-based behavior evaluation

Payoff functions to evaluate alternatives

Choice can be location-dependent

Location-based SW: modeling challenges


Location based sw features to support

Location-based SW: features to support

Location identification

Instantiate a location model

Location-based behavior adaptation

Select the bestpossible behavior to achieve the goals

Location-based information processing

Information request

Relevant information extraction

Information delivery


Location based sw features to support1

Location-based SW: features to support

Act on behalf of users

Location-based SW represents the userwheninteractingwithother location actors

Personalization

Eachuserhas a profile and preferences


Tropos for location based sw goal models

Tropos for location-based SW: goal models

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22/10/2014


Tropos for location based sw benefits

Tropos for location-based SW: benefits

Goal models provide:

High-level goals decomposition to discover alternatives.

Modeling of the problem domain

High level of abstraction that justifies why software is needed.

Modeling of location at the social level (dependencies)

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Tropos for location based sw limits

Tropos for location-based SW: limits

The actors network is static

Location is dynamic

Actor/Resource modeling is limited: no means to express

Availability

Constraints on dependencies

More actors able to fulfill the same goal

No specification of where an alternative is:

Applicable / Forbidden

Recommended

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Our solution: Location-based Tropos


Location based tropos

Location-based Tropos

Location-based (LB) goal models contain variation points annotated with location properties:

LB Or-Decomposition: the basic variability construct to express alternative goal decompositions

LB contribution: contributions to softgoals is location-based

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L1: a terminal is free, has a language in common with the passenger, ...

L2: the railway station has a wireless network and passenger’s PDA support WiFi, ...

L4: low expertise in using PDA, No PDA touch screen.

L3: good expertise in using PDAs and PDA has touch screen


Location based tropos1

Location-based Tropos

LB dependency: the actor may depend on other actors in certain locations.

LB Goal-Activation: location triggers goals.

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L6: the assistant is idle, has a language in common with the requesting passenger, ...

L5: the web-site enables payment with the customer credit card’s type


Location based tropos2

Location-based Tropos

LB And-Decomposition: not all and-decomposition sub-goals are needed in some location.

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L7: the passenger is not familiar with terminals


Location based tropos process

Location-based Tropos process

Model the social structure of a location class

Actors and dependencies

Identify mobile actors

Those actors that need location-based SW

Assign a system-to-be actor to each mobile actor

Use goal analysis to define the rationale

Identify the variation points

Assign location properties to variation points

Derive a location model from location properties


Location based tropos3

Location-based Tropos

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Location-based goal model

Location model


Location based analysis

Location-based analysis

Location model and Location Properties have been formalized using Datalog¬

Location properties satisfiability have been tested using DLV Solver.

An instance of the location model implies a set of goal satisfaction alternatives.


Location based analysis1

Location-based analysis

Location-based Goal Satisfiability (LGS)

Is a goal satisfiable in a certain location?

Location Property Satisfability (LPS)

What a certain location lacks for satisfying a goal!

Preference Analysis (PA): Preferences can be specified over softgoals [Liaskos et al., 2006] to choose when:

There is more than one alternative to satisfy a Goal in one location.

More than one Location modification is possible to make a goal satisfiable.

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Conclusions and future work

Conclusions and Future work

Conclusions

We have shown particularity and importance of modeling location variability in location-based SW

We addressed some conceptual modeling challenges

Modifying and extending Tropos

We defined three formal analysis techniques

Future work

Refine the modeling framework

Choose an expressive enough formal language

Evaluate on a real-world case study

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Raian ali fabiano dalpiaz paolo giorgini

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R. Ali, F. Dalpiaz, P. Giorgini

Thank you!

Questions?

Raian Ali – [email protected]

Fabiano Dalpiaz – [email protected]

Paolo Giorgini – [email protected]


References 1

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References (1)

  • [Yau et al., 2006] Yau, S., Liu, J.: Hierarchical situation modeling and reasoning for pervasive computing. Proceedings of 3rd Workshop on Software Technologies for Future Embedded and Ubiquitous Systems (SEUS) (2006) 5-10

  • [Henricksen et al., 2004] Henricksen, K., Indulska, J.: A software engineering framework for context-aware pervasive computing. PerCom (2004) 77–86 5.

  • [Wang et al., 2004] Wang, X.H., Zhang, D.Q., Gu, T., Pung, H.K.: Ontology based context modeling and reasoning using owl. In: PERCOMW ’04: Proceedings of the Second IEEE Annual Conference on Pervasive Computing and Communications Workshops, Washington, DC, USA, IEEE Computer Society (2004) 18–22

  • [Pohl et al., 2005] Pohl, K., Böckle, G., van der Linden, F.: Software Product Line Engineering: Foundations,Principles, and Techniques. Springer (2005)

  • [Kang et al., 1998] Kang, K., Kim, S., Lee, J., Kim, K., Shin, E., Huh, M.: Form: A feature-oriented reuse method with domain-specific reference architectures. Annals of Software Engineering 5 (1998) 143–168

  • [Bresciani et al., 2004] Bresciani, P., Perini, A., Giorgini, P., Giunchiglia, F., Mylopoulos, J.: Tropos: An agent oriented software development methodology. Autonomous Agents and Multi-Agent Systems 8(3) (2004) 203–236


References 2

References (2)

[Yu, 1995] Yu, E.: Modelling strategic relationships for process reengineering. Ph.D. Thesis, University of Toronto (1995)

[Liaskos et al., 2006] Liaskos, S., McIlraith, S., Mylopoulos, J.: Representing and reasoning with preference requirements using goals. Technical report, Dept. of Computer Science, University of Toronto (2006) ftp://ftp.cs.toronto.edu/pub/reports/csrg/542.

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Location based tropos metamodel

Location-based Tropos: metamodel

Tropos

Loc-based Tropos


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