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Previous issue date: 2017-07-28 === A sociedade moderna, progressivamente, proporciona ambientes sociot?cnicos com sistemas
complexos. Esses sistemas s?o complexos por conta do grande n?mero de partes
que interagem de modo n?o simples, dada as propriedades dessas partes e das leis que
regem essas intera??es. Al?m dessa circunst?ncia, trabalhos da Engenharia de Software
refor?am que o universo das informa??es necess?rias para realizar uma modelagem ? mais
amplo, e envolve mais dimens?es das j? consolidadas: est?tica e din?mica. Assim, surge
o framework iStar com uma ontologia delineada para capturar e representar informa??es
intencionais e sociais do ambiente analisado em dois modelos gr?ficos: Depend?ncia Estrat?gica (SD - Strategic Dependency ) e Racioc?nio Estrat?gico (SR - Strategic Rationale ).
Entretanto, esse mesmo framework n?o oferece alternativas para melhorar a compreens?o
dos seus modelos gr?ficos, quando esses representam um grande n?mero de partes desses
ambientes, ou seja, sistemas complexos. Diante disso, o objetivo desta disserta??o foi
oferecer uma alternativa ao framework iStar para lidar com a complexidade proporcionada
pelos sistemas complexos, desta forma, influenciar positivamente a compreens?o e o
aprendizado dos modelos iStar. Com esse fim, foi desenvolvida uma nota??o textual para
compreender as informa??es sociais atrav?s de uma estrutura interdependente. Na avalia-
??o desenvolvida, observou-se a relev?ncia dessa nota??o textual para os modelos gr?ficos
da seguinte forma: (i) uma alternativa complementar para leitura dos modelos gr?ficos,
como tamb?m, (ii) a import?ncia da constru??o desses modelos a partir de composi??es
de estruturas interdependentes. === A modern society, progressively, provides increasingly sociotechnical environments through
of complex systems. This complexity is to due to the large number of parties interacting
in a non-simple way, given the properties of these parts and the laws governing
these interactions. In addition to this circumstance, the Software Engineering reinforces
that the universe of information needed to perform a broader modeling, and involves
more dimensions of already consolidated: static and dynamic. Thus, the iStar framework
emerges with an ontology capable of capturing and represent intentional and social information
of the environment analyzed in two graphic models: Strategic Dependency (SD)
and Strategic Reasoning (SR). However, this same framework does not offer alternatives
to improve the understanding of its graphic models, when these represent a large number
of parts of these environments. Therefore, the objective of this dissertation was to offer an
alternative to the iStar framework to deal with the complexity provided by the complex
systems, in order to positively influence the understanding and learning of the iStar models.
To this end, a textual notation has been developed to understand social information
through an interdependent structure. In the developed evaluation, it was observed the
relevance of this textual notation for the graphic models as follows: (i) a complementary
alternative for reading of the graphic models, as well as (ii) the importance of building
these models from interdependent structures.
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