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Static slicing of Use Case Maps requirements models

Overview of attention for article published in Software and Systems Modeling, June 2018
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Mentioned by

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1 X user

Citations

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4 Dimensions

Readers on

mendeley
20 Mendeley
Title
Static slicing of Use Case Maps requirements models
Published in
Software and Systems Modeling, June 2018
DOI 10.1007/s10270-018-0680-7
Authors

Taha Binalialhag, Jameleddine Hassine, Daniel Amyot

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 20 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 20 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 4 20%
Professor > Associate Professor 2 10%
Student > Master 2 10%
Student > Doctoral Student 1 5%
Professor 1 5%
Other 2 10%
Unknown 8 40%
Readers by discipline Count As %
Computer Science 13 65%
Unknown 7 35%
Attention Score in Context

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 07 July 2018.
All research outputs
#19,246,640
of 23,849,058 outputs
Outputs from Software and Systems Modeling
#444
of 721 outputs
Outputs of similar age
#257,202
of 331,310 outputs
Outputs of similar age from Software and Systems Modeling
#9
of 10 outputs
Altmetric has tracked 23,849,058 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 721 research outputs from this source. They receive a mean Attention Score of 2.2. This one is in the 3rd percentile – i.e., 3% of its peers scored the same or lower than it.
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 331,310 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 12th percentile – i.e., 12% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 10 others from the same source and published within six weeks on either side of this one.