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Requirements for tools for comprehending highly specialized assembly language code and how to elicit these requirements

Overview of attention for article published in Requirements Engineering, October 2014
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (67th percentile)

Mentioned by

facebook
1 Facebook page
wikipedia
1 Wikipedia page

Citations

dimensions_citation
3 Dimensions

Readers on

mendeley
30 Mendeley
Title
Requirements for tools for comprehending highly specialized assembly language code and how to elicit these requirements
Published in
Requirements Engineering, October 2014
DOI 10.1007/s00766-014-0214-y
Authors

Jennifer Baldwin, Alvin Teh, Elisa Baniassad, Dirk van Rooy, Yvonne Coady

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 30 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Netherlands 1 3%
United States 1 3%
Unknown 28 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 27%
Student > Doctoral Student 4 13%
Student > Master 3 10%
Student > Bachelor 2 7%
Student > Postgraduate 2 7%
Other 5 17%
Unknown 6 20%
Readers by discipline Count As %
Computer Science 14 47%
Engineering 3 10%
Psychology 3 10%
Business, Management and Accounting 1 3%
Materials Science 1 3%
Other 1 3%
Unknown 7 23%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 November 2017.
All research outputs
#7,202,867
of 22,766,595 outputs
Outputs from Requirements Engineering
#52
of 199 outputs
Outputs of similar age
#79,021
of 255,208 outputs
Outputs of similar age from Requirements Engineering
#1
of 4 outputs
Altmetric has tracked 22,766,595 research outputs across all sources so far. This one has received more attention than most of these and is in the 67th percentile.
So far Altmetric has tracked 199 research outputs from this source. They receive a mean Attention Score of 2.9. This one has gotten more attention than average, scoring higher than 73% 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 255,208 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 67% of its contemporaries.
We're also able to compare this research output to 4 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them