Title |
Towards building a universal defect prediction model with rank transformed predictors
|
---|---|
Published in |
Empirical Software Engineering, August 2015
|
DOI | 10.1007/s10664-015-9396-2 |
Authors |
Feng Zhang, Audris Mockus, Iman Keivanloo, Ying Zou |
Mendeley readers
The data shown below were compiled from readership statistics for 94 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 1 | 1% |
Unknown | 93 | 99% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Master | 34 | 36% |
Student > Ph. D. Student | 16 | 17% |
Lecturer | 6 | 6% |
Student > Doctoral Student | 5 | 5% |
Professor > Associate Professor | 4 | 4% |
Other | 13 | 14% |
Unknown | 16 | 17% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 50 | 53% |
Social Sciences | 7 | 7% |
Arts and Humanities | 6 | 6% |
Engineering | 6 | 6% |
Psychology | 2 | 2% |
Other | 4 | 4% |
Unknown | 19 | 20% |
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 28 November 2016.
All research outputs
#20,355,479
of 22,903,988 outputs
Outputs from Empirical Software Engineering
#624
of 706 outputs
Outputs of similar age
#223,675
of 266,291 outputs
Outputs of similar age from Empirical Software Engineering
#5
of 10 outputs
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So far Altmetric has tracked 706 research outputs from this source. They receive a mean Attention Score of 4.8. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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We're also able to compare this research output to 10 others from the same source and published within six weeks on either side of this one. This one has scored higher than 5 of them.