↓ Skip to main content

A Framework for Evaluating the Results of the SZZ Approach for Identifying Bug-Introducing Changes

Overview of attention for article published in IEEE Transactions on Software Engineering, July 2017
Altmetric Badge

Mentioned by

facebook
1 Facebook page

Readers on

mendeley
87 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.
Article details
Title
A Framework for Evaluating the Results of the SZZ Approach for Identifying Bug-Introducing Changes
Published in
IEEE Transactions on Software Engineering, July 2017
DOI 10.1109/tse.2016.2616306
Authors

Login to access the Attention Digest and the Sentiment Analysis related to this output.

Timeline Attention over time Attention Score history
Login to access the full charts related to this output.
Activity
Login to access the full charts related to this output.
Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 87 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Login to view Mendeley reader trends over time.

Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 87 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Master 19 22%
Student > Ph. D. Student 16 18%
Student > Bachelor 9 10%
Student > Doctoral Student 7 8%
Researcher 6 7%
Other 13 15%
Unknown 17 20%
Readers by discipline
Readers by discipline Count As %
Computer Science 56 64%
Engineering 3 3%
Business, Management and Accounting 2 2%
Unspecified 1 1%
Agricultural and Biological Sciences 1 1%
Other 1 1%
Unknown 23 26%
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 08 May 2017.
All research outputs
#22,760,732
of 25,377,790 outputs
Outputs from IEEE Transactions on Software Engineering
#5,962
of 6,368 outputs
Outputs of similar age
#284,312
of 324,702 outputs
Outputs of similar age from IEEE Transactions on Software Engineering
#51
of 57 outputs
Altmetric has tracked 25,377,790 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 6,368 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 1st percentile – i.e., 1% 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 324,702 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 57 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.