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Mining Version Histories for Detecting Code Smells

Overview of attention for article published in IEEE Transactions on Software Engineering, May 2015
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (62nd percentile)
  • Good Attention Score compared to outputs of the same age and source (67th percentile)

Mentioned by

twitter
1 X user
wikipedia
1 Wikipedia page

Readers on

mendeley
189 Mendeley
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Article details
Title
Mining Version Histories for Detecting Code Smells
Published in
IEEE Transactions on Software Engineering, May 2015
DOI 10.1109/tse.2014.2372760
Authors

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Timeline Attention over time Attention Score history
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Activity
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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 demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 189 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
United States 2 1%
Brazil 2 1%
Norway 1 <1%
Korea, Republic of 1 <1%
Indonesia 1 <1%
France 1 <1%
Spain 1 <1%
Germany 1 <1%
Canada 1 <1%
Other 0 0%
Unknown 178 94%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Master 47 25%
Student > Ph. D. Student 37 20%
Student > Doctoral Student 13 7%
Student > Bachelor 13 7%
Professor > Associate Professor 11 6%
Other 27 14%
Unknown 41 22%
Readers by discipline
Readers by discipline Count As %
Computer Science 126 67%
Engineering 8 4%
Arts and Humanities 3 2%
Mathematics 1 <1%
Business, Management and Accounting 1 <1%
Other 6 3%
Unknown 44 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 24 February 2016.
All research outputs
#11,631,900
of 33,953,699 outputs
Outputs from IEEE Transactions on Software Engineering
#3,413
of 7,770 outputs
Outputs of similar age
#110,883
of 305,835 outputs
Outputs of similar age from IEEE Transactions on Software Engineering
#17
of 59 outputs
Altmetric has tracked 33,953,699 research outputs across all sources so far. This one has received more attention than most of these and is in the 64th percentile.
So far Altmetric has tracked 7,770 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.0. This one has gotten more attention than average, scoring higher than 54% 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 305,835 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 62% of its contemporaries.
We're also able to compare this research output to 59 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 67% of its contemporaries.