Loc-based Variability for Mobile
Information Systems
Raian Ali, Fabiano Dalpiaz, Paolo Giorgini
CAiSE’08
18-20 June 2008
2
R. Ali, F. Dalpiaz, P. Giorgini
Talk outline
• Location-based MobIS
• Limits of existing modeling techniques
▫ Context Models
▫ Software Variability Models
▫ Goal models
• Location-based goal modeling
• Location-based analysis
• Conclusions
29/07/2017
R. Ali, F. Dalpiaz, P. Giorgini
29/07/2017
Location-based MobIS
[Streizt et al., 2005] [Weiser, 1991] [Krogstie et al., 2004]
R. Ali, F. Dalpiaz, P. Giorgini
29/07/2017
Limits of existing modeling techniques
Context models
[Yau et al., 2006]
[Henricksen et al., 2004]
[Wang et al., 2004]
R. Ali, F. Dalpiaz, P. Giorgini
29/07/2017
Limits of existing modeling techniques
Context models
• Several context models have been proposed.
• Without specifying the relation between context and its
use, we cannot say
▫ Why context is needed
▫ Which is the relevant part of context
▫ How context influences software derivation
• Context awareness is mainly focused on the software
domain, not on the problem domain.
R. Ali, F. Dalpiaz, P. Giorgini
29/07/2017
Limits of existing modeling techniques
Software variability models
[Kang et al., 1998] [Pohl et al., 2005]
R. Ali, F. Dalpiaz, P. Giorgini
29/07/2017
Limits of existing modeling techniques
Software variability models
• By modeling variability, 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 in MobIS we need:
▫ Autonomous selection between features
▫ Higher level of abstraction that justifies the features
R. Ali, F. Dalpiaz, P. Giorgini
29/07/2017
Limits of existing modeling techniques
Goal models
[Yu, 1995] [Bresciani et al., 2004]
R. Ali, F. Dalpiaz, P. Giorgini
29/07/2017
Limits of existing modeling techniques
Goal models
• Goal models provide:
▫ High-level goals decomposition to discover alternatives.
▫ Good modeling of the problem domain
▫ Higher level of abstraction justifies why software is needed.
• … but:
▫ Goal models do not specify where an alternative is:
 Applicable
 Recommended
R. Ali, F. Dalpiaz, P. Giorgini
29/07/2017
Location-based goal modeling
• Location-based (LB) goal models contain variability
points annotated with location properties:
1. LB Or-Decomposition: the basic variability construct to
express alternative goal decompositions
2.LB contribution: contributions to soft-goals depends on the
location.
3.LB dependency: the actor may depend on other actors in
certain locations.
4.LB Goal-Activation: location changes trigger (activate,
stop) goals.
5.LB And-Decomposition: not all and-decomposition subgoals are needed in some location.
R. Ali, F. Dalpiaz, P. Giorgini
29/07/2017
Location-based goal modeling
Location-based goal model
Location model
R. Ali, F. Dalpiaz, P. Giorgini
29/07/2017
Location-based analysis
• Loc-based Goal Satisfiability (LGS)
▫ Is a goal satisfiable in a certain location instance?
• Location Property Satisfability (LPS)
▫ What a Location lacks for satisfying a Goal!
• Preference Analysis (PA): Preferences can be specified
over softgoals [Liaskos et al., 2006] to choose when:
▫ More than one alternative to satisfy a Goal in a location.
▫ More than one Location modification is possible to make a
goal satisfiable.
R. Ali, F. Dalpiaz, P. Giorgini
29/07/2017
Conclusions
• We exploit i*/Tropos goal models to model locationbased MobIS
▫ We associate context information to variability points
▫ We support an automated derivation of loc-based software
• We introduce three analysis techniques
▫ Loc-based goal satisfiability
▫ Location property satisfiability
▫ Preference based alternatives adopting
R. Ali, F. Dalpiaz, P. Giorgini
29/07/2017
Future work
• Finding suitable abstraction for modeling location at the
social level.
• Looking for a suitable formalization
• Formalizing the whole i*/Tropos loc-based GM
• Positioning our proposed models into the whole MobIS
SDLC.
• Developing different case studies taken from different
domains
R. Ali, F. Dalpiaz, P. Giorgini
29/07/2017
References (1)
• [Streizt et al., 2005] Streitz, N., Nixon, P.: The disappearing computer. Commun.
ACM 48(3) (2005)
• [Weiser, 1991] Weiser, M.: The computer for the twenty-first century. Scientific
American 265(3) (1991)94–104
• [Krogstie et al., 2004]Krogstie, J., Lyytinen, K., Opdahl, A., Pernici, B., Siau, K.,
Smolander, K.: Research areas and challenges for mobile information systems.
International Journal of Mobile Communications 2(3) (2004) 220–234
• [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
R. Ali, F. Dalpiaz, P. Giorgini
29/07/2017
References (2)
• [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
• [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.