| Title |
Automatic repair of real bugs in java: a large-scale experiment on the defects4j dataset
|
|---|---|
| Published in |
Empirical Software Engineering, October 2016
|
| DOI | 10.1007/s10664-016-9470-4 |
| Authors |
Matias Martinez, Thomas Durieux, Romain Sommerard, Jifeng Xuan, Martin Monperrus |
X Demographics
The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Russia | 1 | 17% |
| United States | 1 | 17% |
| Sweden | 1 | 17% |
| Unknown | 3 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 50% |
| Scientists | 2 | 33% |
| Science communicators (journalists, bloggers, editors) | 1 | 17% |
Mendeley readers
The data shown below were compiled from readership statistics for 112 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | <1% |
| Unknown | 111 | 99% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 37 | 33% |
| Student > Master | 22 | 20% |
| Researcher | 11 | 10% |
| Professor > Associate Professor | 4 | 4% |
| Student > Doctoral Student | 4 | 4% |
| Other | 13 | 12% |
| Unknown | 21 | 19% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 75 | 67% |
| Engineering | 9 | 8% |
| Biochemistry, Genetics and Molecular Biology | 1 | <1% |
| Psychology | 1 | <1% |
| Unspecified | 1 | <1% |
| Other | 0 | 0% |
| Unknown | 25 | 22% |
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 12 November 2018.
All research outputs
#7,538,395
of 22,999,744 outputs
Outputs from Empirical Software Engineering
#292
of 707 outputs
Outputs of similar age
#114,650
of 314,439 outputs
Outputs of similar age from Empirical Software Engineering
#17
of 28 outputs
Altmetric has tracked 22,999,744 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 707 research outputs from this source. They receive a mean Attention Score of 4.8. This one has gotten more attention than average, scoring higher than 55% 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 314,439 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 51% of its contemporaries.
We're also able to compare this research output to 28 others from the same source and published within six weeks on either side of this one. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.