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Applying static code analysis for domain-specific languages

Overview of attention for article published in Software & Systems Modeling, April 2019
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#20 of 417)
  • Good Attention Score compared to outputs of the same age (70th percentile)
  • High Attention Score compared to outputs of the same age and source (93rd percentile)

Mentioned by

twitter
7 tweeters

Readers on

mendeley
8 Mendeley
Title
Applying static code analysis for domain-specific languages
Published in
Software & Systems Modeling, April 2019
DOI 10.1007/s10270-019-00729-w
Authors

Iván Ruiz-Rube, Tatiana Person, Juan Manuel Dodero, José Miguel Mota, Javier Merchán Sánchez-Jara

Twitter Demographics

The data shown below were collected from the profiles of 7 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 8 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 8 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 4 50%
Student > Master 2 25%
Student > Doctoral Student 1 13%
Student > Ph. D. Student 1 13%
Readers by discipline Count As %
Unspecified 4 50%
Computer Science 3 38%
Engineering 1 13%

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 October 2019.
All research outputs
#2,994,592
of 13,615,200 outputs
Outputs from Software & Systems Modeling
#20
of 417 outputs
Outputs of similar age
#73,766
of 255,430 outputs
Outputs of similar age from Software & Systems Modeling
#2
of 33 outputs
Altmetric has tracked 13,615,200 research outputs across all sources so far. Compared to these this one has done well and is in the 77th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 417 research outputs from this source. They receive a mean Attention Score of 1.7. This one has done particularly well, scoring higher than 94% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 255,430 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 70% of its contemporaries.
We're also able to compare this research output to 33 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 93% of its contemporaries.