Conceptual Modeling and Integration of Static and Dynamic Aspects of Service Architectures

Gustas, Remigijus

doi:10.1007/978-3-642-16496-5_2

Cited by 11 publications

(10 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Despite the dominance of UML there is a certain degree of difficulty in understanding a system represented by means of UML diagrams (Bavota et al, 2011;Otero & Dolado, 2004;Siau & Cao, 2001;Siau, Erickson, & Lee, 2005). Previous research has indicated several reasons: among which (1) the level of structural complexity of UML exceeding the limits of human working memory (cognitive load) in terms of the ability for effective information processing (Cruz-Lemus, Genero, & Piattini, 2008;Cruz-Lemus, Maes, Genero, Poels, & Piattini, 2010;Erickson & Siau, 2007;Wilmont, Hengeveld, Barendsen, & Hoppenbrouwers, 2013); and (2) lack of comprehension methodologies (Erickson & Siau, 2007) and, in particular, its impreciseness about the combination of interactive, structural and behavioral aspects together in a single model (Gustas, 2010). Furthermore, (3) it is not easy to find relevant subsets suitable for a modeling goal.…”

Section: Introductionmentioning

confidence: 99%

Process-mining enabled feedback: “Tell me what I did wrong” vs. “tell me how to do it right”

Sedrakyan

Weerdt

Snoeck

2016

Computers in Human Behavior

View full text Add to dashboard Cite

Fast advancement of technology has led to an increased interest for using information technology to provide feedback based on learning behavior observations. This work outlines a novel approach for analyzing behavioral learner data through the application of process mining techniques specifically targeting a complex problem solving process. We realize this in the context of one particular learning case, namely, domain modeling. This work extends our previous research on process-mining analysis of domain modeling behavior of novices by elaborating with new insights from a replication study enhanced with an extra observation on how novices verify/validate models. The findings include a set of typical modeling and validation patterns that can be used to improve teaching guidance for domain modeling courses. From a scientific viewpoint, the results contribute to improving our knowledge on the cognitive aspects of problem-solving behavior of novices in the area of domain modeling, specifically regarding process-oriented feedback as opposed to traditional outcome feedback (is a solution correct? Why (not)?) usually applied in this type of courses. Ultimately, the outcomes of the work can be inspirational outside of the area of domain modeling as learning event data is becoming readily available through virtual learning environments and other information systems.

show abstract

Section: Introductionmentioning

confidence: 99%

Process-mining enabled feedback: “Tell me what I did wrong” vs. “tell me how to do it right”

Sedrakyan

Weerdt

Snoeck

2016

Computers in Human Behavior

View full text Add to dashboard Cite

show abstract

“…In a previous paper [2] we already discussed a set of issues related to the widely accepted standard UML [20,23,24,25,26]. In its current form UML performs poor in supporting an educational perspective.…”

Section: Modeling Environmentmentioning

confidence: 99%

Feedback-Enabled MDA-Prototyping Effects on Modeling Knowledge

Sedrakyan

Snoeck

2013

Enterprise, Business-Process and Information Systems Modeling

View full text Add to dashboard Cite

This paper describes the effects of a feedback-enabled MDA prototyping tool on the validation cycle for conceptual models. We observe the effects of such prototyping method on learning outcomes of novice modelers. The impact is assessed based on the quality dimensions introduced by Conceptual Modeling Quality Framework (CMQF), more specifically with respect to semantic quality being affected by modeling knowledge. The current work proposes an extension to the techniques introduced in previous work in particular experimenting with the prototyping tool by novice modelers. A positive impact has been observed on the learning achievements of novice modelers improving both modeling and language knowledge.

show abstract

“…(Erickson, Siau, 2007) present the complexity metric of the UML which scores from 2 to 11 times more complex than those of other methods due to the diversity of supported constructs and diagrams. Among the other fundamental deficiencies of UML is that it is unclear how to combine interactive, structural and behavioural aspects together in a single model (Gustas, 2010). Furthermore, (Buckl et al, 2010) points out the "noisiness" of modelling languages with various concepts, that can result in misusing concepts and creation of unintended models, i.e.…”

Section: Problem Domainmentioning

confidence: 99%

A PIM-to-Code Requirements Engineering Framework

Sedrakyan¹,

Snoeck²

2013

Proceedings of the 1st International Conference on Model-Driven Engineering and Software Development

View full text Add to dashboard Cite

Abstract:The complexity of Model-driven engineering (MDE) leads to a limited adoption in practice. In this paper we argue that MDE offers "low hanging fruit" if creating executable UML models allowing core functionality prototyping is targeted rather than developing full-fledged information systems. This paper describes an environment for designing and validating conceptual business models using the model-driven architecture (MDA). The deliverable of the proposed modelling environment is an executable platform independent model (EPIM) that is further tested and validated through an MDA-based simulation feature. The proposed environment addresses a set of challenges associated with 1. shortcomings of the UML for being technically too complex for conceptual modelling goals as well as for being imprecise for rapid prototyping; 2. difficulties of MDE adoption due to the large set of required skills to adopt the key MDA standards such as the UML, MOF and XMI. The paper aims to introduce the current work and identify the needs for future research.

show abstract

Conceptual Modeling and Integration of Static and Dynamic Aspects of Service Architectures

Cited by 11 publications

References 16 publications

Process-mining enabled feedback: “Tell me what I did wrong” vs. “tell me how to do it right”

Process-mining enabled feedback: “Tell me what I did wrong” vs. “tell me how to do it right”

Feedback-Enabled MDA-Prototyping Effects on Modeling Knowledge

A PIM-to-Code Requirements Engineering Framework

Contact Info

Product

Resources

About