Identifying the Weaknesses of UML Class Diagrams during Data Model Comprehension

Bavota, Gabriele; Gravino, Carmine; Oliveto, Rocco; Lucia, Andrea De; Tortora, Genoveffa; Genero, Marcela; Cruz-Lemus, José A.

doi:10.1007/978-3-642-24485-8_13

Cited by 13 publications

(12 citation statements)

References 16 publications

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“…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).…”

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

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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.

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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

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“…According to the first two works [15] [16], the authors suggest that the CD notation is generally more comprehensible than the EER notation. However, in the third work [17], the authors conclude that the understanding of EER model is significantly higher than CD if "composite attribute", "multi-value attribute" and "weak entity" are required in a modeling. To summarize this discussion, we think that any comparison between the EER model and the CD can provide results to debate and arguing, and the choice for a particular notation rather than other is a matter of preference or project contingency.…”

Section: Fig 1 Constructors Of the Eer Modelmentioning

confidence: 95%

EERMM: A Metamodel for the Enhanced Entity-Relationship Model

Fidalgo¹,

Souza²,

España³

et al. 2012

Conceptual Modeling

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A metamodel describes the elements of a model, the relationships between them, and the structuring rules that constraint the model elements and the way they are arranged/related in order to respect the domain rules. That is, a metamodel provides an abstract syntax to distinguish between valid and invalid models. Although the Enhanced Entity-Relationship (EER) model has been extensively researched, and various extensions and enhancements have been proposed, to the best of our knowledge, a metamodel for the EER model, based on the classical notation of Chen, has not been proposed yet. That is, we have found no evidence of a metamodel that gives a precise and expressive definition of constructors and constructions needed to create, interchange or transform valid EER models. With aim of overcoming these shortcoming, in this paper we propose an expressive metamodel for EER modeling, named EER MetaModel (EERMM), which provides a novel perspective for scientific researches and industrial applications that need an EER metamodel as a starting point. As a proof of concept, we have implemented a CASE tool (EERCASE) according to our metamodel and, by exploiting this tool, we have designed an EER schema that makes use of all constructors of the EER model.

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“…The considered systems are hosted on GitHub and built on the TravisCI [32] platform. We followed the methodology of Bavota et al [3] to select systems that developers can easily get familiar with and that are, at the same time, representative for real software systems. While our selected systems have less than 500K lines of code, they are very popular (more than 100 stars on GitHub) and frequently built (more than 100 builds on the master branch).…”

Section: Contextmentioning

confidence: 99%

Un-break my build

Vassallo

Proksch

Zemp

et al. 2018

Proceedings of the 26th Conference on Program Comprehension

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Continuous integration is an agile software development practice. Instead of integrating features right before a release, they are constantly being integrated in an automated build process. This shortens the release cycle, improves software quality, and reduces time to market. However, the whole process will come to a halt when a commit breaks the build, which can happen for several reasons, e.g., compilation errors or test failures, and fixing the build suddenly becomes a top priority. Developers not only have to find the cause of the build break and fix it, but they have to be quick in all of it to avoid a delay for others. Unfortunately, these steps require deep knowledge and are often time consuming. To support developers in fixing a build break, we propose Bart, a tool that summarizes the reasons of the build failure and suggests possible solutions found on the Internet. We will show in a case study with eight participants that developers find Bart useful to understand build breaks and that using Bart substantially reduces the time to fix a build break, on average by 41%.

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Identifying the Weaknesses of UML Class Diagrams during Data Model Comprehension

Cited by 13 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”

EERMM: A Metamodel for the Enhanced Entity-Relationship Model

Un-break my build

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