| Title |
A comprehensive study of pseudo-tested methods
|
|---|---|
| Published in |
Empirical Software Engineering, September 2018
|
| DOI | 10.1007/s10664-018-9653-2 |
| Authors |
Oscar Luis Vera-Pérez, Benjamin Danglot, Martin Monperrus, Benoit Baudry |
X Demographics
The data shown below were collected from the profiles of 9 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Netherlands | 1 | 11% |
| Canada | 1 | 11% |
| Cuba | 1 | 11% |
| France | 1 | 11% |
| Unknown | 5 | 56% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 7 | 78% |
| Science communicators (journalists, bloggers, editors) | 1 | 11% |
| Scientists | 1 | 11% |
Mendeley readers
The data shown below were compiled from readership statistics for 26 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 26 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Doctoral Student | 3 | 12% |
| Student > Ph. D. Student | 3 | 12% |
| Researcher | 3 | 12% |
| Student > Master | 3 | 12% |
| Student > Postgraduate | 2 | 8% |
| Other | 2 | 8% |
| Unknown | 10 | 38% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 13 | 50% |
| Veterinary Science and Veterinary Medicine | 1 | 4% |
| Chemical Engineering | 1 | 4% |
| Sports and Recreations | 1 | 4% |
| Unknown | 10 | 38% |
Attention Score in Context
This research output has an Altmetric Attention Score of 10. 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 17 March 2021.
All research outputs
#3,466,304
of 24,780,938 outputs
Outputs from Empirical Software Engineering
#71
of 756 outputs
Outputs of similar age
#67,687
of 347,248 outputs
Outputs of similar age from Empirical Software Engineering
#4
of 18 outputs
Altmetric has tracked 24,780,938 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 756 research outputs from this source. They receive a mean Attention Score of 4.7. This one has done particularly well, scoring higher than 90% 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 347,248 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 80% of its contemporaries.
We're also able to compare this research output to 18 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 83% of its contemporaries.