↓ Skip to main content

How developers engage with static analysis tools in different contexts

Overview of attention for article published in Empirical Software Engineering, November 2019
Altmetric Badge

About this Attention Score

  • Good Attention Score compared to outputs of the same age (67th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (52nd percentile)

Mentioned by

twitter
6 tweeters

Citations

dimensions_citation
3 Dimensions

Readers on

mendeley
23 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
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

Twitter Demographics

The data shown below were collected from the profiles of 6 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 23 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 23 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 22%
Researcher 4 17%
Student > Master 3 13%
Student > Doctoral Student 2 9%
Student > Bachelor 1 4%
Other 3 13%
Unknown 5 22%
Readers by discipline Count As %
Computer Science 13 57%
Unspecified 1 4%
Engineering 1 4%
Unknown 8 35%

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
#3,924,241
of 15,099,074 outputs
Outputs from Empirical Software Engineering
#118
of 493 outputs
Outputs of similar age
#111,481
of 345,230 outputs
Outputs of similar age from Empirical Software Engineering
#9
of 19 outputs
Altmetric has tracked 15,099,074 research outputs across all sources so far. This one has received more attention than most of these and is in the 73rd percentile.
So far Altmetric has tracked 493 research outputs from this source. They receive a mean Attention Score of 4.0. This one has done well, scoring higher than 76% 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 345,230 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 19 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 52% of its contemporaries.