Raian Ali, Fabiano Dalpiaz, Paolo Giorgini

Location-based Software Modeling and Analysis:

Tropos-based Approach

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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

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Research question• 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 analyze location-based SW?

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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• 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

Feature models [Kang et al., 1998]

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1. Location modeling constructs ▫ What is the conceptual framework?

2. Location relevancy▫ What should be modeled?

3. Location rules▫ Constraints of the specific location

4. Location-based behavior▫ Different behaviors are enabled/disabled

depending on the current location

Location-based SW: modeling challenges

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5. Hierarchical behaviors construction▫Avoid “one location, one behavior” cases

6. Location-based behavior evaluation▫Payoff functions to evaluate alternatives▫Choice can be location-dependent

Location-based SW: modeling challenges

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Location-based SW: features to support

1. Location identification▫Instantiate a location model

2. Location-based behavior adaptation▫Select the best possible behavior to achieve

the goals3. Location-based information processing

▫Information request▫Relevant information extraction▫Information delivery

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Location-based SW: features to support

4. Act on behalf of users▫Location-based SW represents the user

when interacting with other location actors5. Personalization

▫Each user has a profile and preferences

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Tropos for location-based SW: goal models

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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• 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 Our solution: Location-

based Tropos

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Location-based Tropos

• Location-based (LB) goal models contain variation points annotated with location properties:1.LB Or-Decomposition: the basic variability construct

to express alternative goal decompositions2.LB contribution: contributions to softgoals is

location-basedL1: 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, ... L3: good expertise

in using PDAs and PDA has touch screen

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

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Location-based Tropos

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

4. LB Goal-Activation: location triggers goals.

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

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

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Location-based Tropos

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

L7: the passenger is not familiar with terminals

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Location-based Tropos process

1. Model the social structure of a location class▫Actors and dependencies

2. Identify mobile actors▫Those actors that need location-based SW

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

▫Use goal analysis to define the rationale4. Identify the variation points

▫Assign location properties to variation points5. Derive a location model from location

properties

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Location-based Tropos

Location-based goal model Location model

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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.

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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▫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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Thank you!

Questions?

Raian Ali – ali@disi.unitn.itFabiano Dalpiaz – dalpiaz@disi.unitn.itPaolo Giorgini – pgiorgio@disi.unitn.it

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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

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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

Tropos

Loc-based Tropos