| Title |
Leveraging annotation-based modeling with Jump
|
|---|---|
| Published in |
Software and Systems Modeling, May 2016
|
| DOI | 10.1007/s10270-016-0528-y |
| Pubmed ID | |
| Authors |
Alexander Bergmayr, Michael Grossniklaus, Manuel Wimmer, Gerti Kappel |
| Abstract |
The capability of UML profiles to serve as annotation mechanism has been recognized in both research and industry. Today's modeling tools offer profiles specific to platforms, such as Java, as they facilitate model-based engineering approaches. However, considering the large number of possible annotations in Java, manually developing the corresponding profiles would only be achievable by huge development and maintenance efforts. Thus, leveragingannotation-based modelingrequires an automated approach capable of generating platform-specific profiles from Java libraries. To address this challenge, we present the fully automated transformation chain realized by Jump, thereby continuing existing mapping efforts between Java and UML by emphasizing on annotations and profiles. The evaluation of Jump shows that it scales for large Java libraries and generates profiles of equal or even improved quality compared to profiles currently used in practice. Furthermore, we demonstrate the practical value of Jump by contributing profiles that facilitate reverse engineering and forward engineering processes for the Java platform by applying it to a modernization scenario. |
X Demographics
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Science communicators (journalists, bloggers, editors) | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 18 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 18 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 3 | 17% |
| Student > Doctoral Student | 2 | 11% |
| Researcher | 2 | 11% |
| Student > Ph. D. Student | 2 | 11% |
| Professor | 1 | 6% |
| Other | 0 | 0% |
| Unknown | 8 | 44% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 9 | 50% |
| Engineering | 1 | 6% |
| Unknown | 8 | 44% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 05 June 2016.
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#19,246,640
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Outputs of similar age from Software and Systems Modeling
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