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How developers engage with static analysis tools in different contexts

Overview of attention for article published in Empirical Software Engineering, November 2019
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (70th percentile)
  • Good Attention Score compared to outputs of the same age and source (75th percentile)

Mentioned by

twitter
6 X users

Citations

dimensions_citation
79 Dimensions

Readers on

mendeley
84 Mendeley
Title
How developers engage with static analysis tools in different contexts
Published in
Empirical Software Engineering, November 2019
DOI 10.1007/s10664-019-09750-5
Authors

Carmine Vassallo, Sebastiano Panichella, Fabio Palomba, Sebastian Proksch, Harald C. Gall, Andy Zaidman

X Demographics

X Demographics

The data shown below were collected from the profiles of 6 X users 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 84 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 84 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 11 13%
Student > Ph. D. Student 9 11%
Student > Bachelor 8 10%
Professor 5 6%
Student > Doctoral Student 4 5%
Other 13 15%
Unknown 34 40%
Readers by discipline Count As %
Computer Science 39 46%
Engineering 4 5%
Business, Management and Accounting 1 1%
Psychology 1 1%
Economics, Econometrics and Finance 1 1%
Other 0 0%
Unknown 38 45%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 26 November 2019.
All research outputs
#6,248,139
of 23,177,498 outputs
Outputs from Empirical Software Engineering
#190
of 710 outputs
Outputs of similar age
#134,142
of 458,595 outputs
Outputs of similar age from Empirical Software Engineering
#2
of 8 outputs
Altmetric has tracked 23,177,498 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 710 research outputs from this source. They receive a mean Attention Score of 4.8. 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 458,595 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 8 others from the same source and published within six weeks on either side of this one. This one has scored higher than 6 of them.