Title |
Improved representation and genetic operators for linear genetic programming for automated program repair
|
---|---|
Published in |
Empirical Software Engineering, January 2018
|
DOI | 10.1007/s10664-017-9562-9 |
Authors |
Vinicius Paulo L. Oliveira, Eduardo Faria de Souza, Claire Le Goues, Celso G. Camilo-Junior |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
Country | Count | As % |
---|---|---|
Sweden | 1 | 33% |
Unknown | 2 | 67% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 1 | 33% |
Members of the public | 1 | 33% |
Science communicators (journalists, bloggers, editors) | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 37 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 37 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 12 | 32% |
Student > Master | 8 | 22% |
Professor | 2 | 5% |
Student > Doctoral Student | 2 | 5% |
Student > Bachelor | 1 | 3% |
Other | 4 | 11% |
Unknown | 8 | 22% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 20 | 54% |
Engineering | 2 | 5% |
Psychology | 1 | 3% |
Agricultural and Biological Sciences | 1 | 3% |
Unknown | 13 | 35% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 May 2019.
All research outputs
#13,517,432
of 23,045,021 outputs
Outputs from Empirical Software Engineering
#395
of 709 outputs
Outputs of similar age
#218,202
of 441,168 outputs
Outputs of similar age from Empirical Software Engineering
#21
of 27 outputs
Altmetric has tracked 23,045,021 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 709 research outputs from this source. They receive a mean Attention Score of 4.8. This one is in the 43rd percentile – i.e., 43% 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 441,168 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 50% of its contemporaries.
We're also able to compare this research output to 27 others from the same source and published within six weeks on either side of this one. This one is in the 22nd percentile – i.e., 22% of its contemporaries scored the same or lower than it.