| Title |
Alleviating patch overfitting with automatic test generation: a study of feasibility and effectiveness for the Nopol repair system
|
|---|---|
| Published in |
Empirical Software Engineering, May 2018
|
| DOI | 10.1007/s10664-018-9619-4 |
| Authors |
Zhongxing Yu, Matias Martinez, Benjamin Danglot, Thomas Durieux, Martin Monperrus |
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 % |
|---|---|---|
| Spain | 1 | 33% |
| Unknown | 2 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 33% |
| Science communicators (journalists, bloggers, editors) | 1 | 33% |
| Members of the public | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 40 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 40 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 12 | 30% |
| Student > Master | 6 | 15% |
| Researcher | 5 | 13% |
| Student > Bachelor | 3 | 8% |
| Student > Postgraduate | 2 | 5% |
| Other | 3 | 8% |
| Unknown | 9 | 23% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 26 | 65% |
| Engineering | 4 | 10% |
| Psychology | 1 | 3% |
| Unknown | 9 | 23% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 22 July 2019.
All research outputs
#14,611,176
of 24,002,307 outputs
Outputs from Empirical Software Engineering
#425
of 734 outputs
Outputs of similar age
#178,369
of 329,377 outputs
Outputs of similar age from Empirical Software Engineering
#12
of 16 outputs
Altmetric has tracked 24,002,307 research outputs across all sources so far. This one is in the 38th percentile – i.e., 38% of other outputs scored the same or lower than it.
So far Altmetric has tracked 734 research outputs from this source. They receive a mean Attention Score of 4.7. This one is in the 40th percentile – i.e., 40% 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 329,377 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 44th percentile – i.e., 44% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 16 others from the same source and published within six weeks on either side of this one. This one is in the 31st percentile – i.e., 31% of its contemporaries scored the same or lower than it.