By Michele Missikoff (auth.), Jolita Ralyté, Xavier Franch, Sjaak Brinkkemper, Stanislaw Wrycza (eds.)
This e-book constitutes the refereed court cases of the twenty fourth overseas convention on complicated details structures Engineering, CAiSE 2012, held in Gdansk, Poland, in June 2012. The forty two revised complete papers, 2 full-length invited papers and four brief educational papers, have been conscientiously reviewed and chosen from 297 submissions. The contributions were grouped into the next topical sections: enterprise technique version research; carrier and part composition; language and versions; approach versions and configuration; technique mining; ontologies; specifications and objective types; compliance; tracking and prediction; prone; case experiences; enterprise method layout; function versions and product traces; and human factors.
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In other words, the comparative complexity analysis neither supports nor refutes the hypothesis that structuring an unstructured process model leads to a higher understandability. 4 Controlled Experiment Considering the ambivalent outcomes produced by the comparative complexity study, we decided to approach the research question with a questionnaire-based, controlled experiment. In this section, we describe its design. Subjects: The experiment was run at Queensland University of Technology in early October 2011.
25] provide a complete characterization of unstructured acyclic process models that are inherently unstructured, based on the RPST decomposition developed by Vanhatalo et al. . Previous research on structuring process models has been consolidated in a tool called BPStruct1 . BPStruct tries to structure a model to the maximum possible extent. The resulting model is then said to be maximally-structured. 3 35 Complexity Metrics and Understandability In addition to formal work on structuring process models, there is a growing body of research on how the understandability of a process model can be evaluated from an empirical perspective.
Deriving knowledge from large data sets presents speciﬁc scaling problems due to a large number of items, dimensions, sources, users, and disparate user communities. A human ability to process visual information can augment the analysis, especially when analytic results are presented in real-time iterative Challenges for Future Platforms, Services and Networked Applications 27 and interactive ways. What we are witnessing is another shift in computing generating information out of distributed data sets in real-time.