| Title |
The impact of rapid release cycles on the integration delay of fixed issues
|
|---|---|
| Published in |
Empirical Software Engineering, November 2017
|
| DOI | 10.1007/s10664-017-9548-7 |
| Authors |
Daniel Alencar da Costa, Shane McIntosh, Christoph Treude, Uirá Kulesza, Ahmed E. Hassan |
X Demographics
The data shown below were collected from the profiles of 16 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 | 3 | 19% |
| Brazil | 2 | 13% |
| United States | 2 | 13% |
| Singapore | 1 | 6% |
| Luxembourg | 1 | 6% |
| New Zealand | 1 | 6% |
| United Kingdom | 1 | 6% |
| Unknown | 5 | 31% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 8 | 50% |
| Members of the public | 7 | 44% |
| Science communicators (journalists, bloggers, editors) | 1 | 6% |
Mendeley readers
The data shown below were compiled from readership statistics for 36 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 36 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 8 | 22% |
| Student > Ph. D. Student | 7 | 19% |
| Student > Doctoral Student | 3 | 8% |
| Researcher | 2 | 6% |
| Other | 1 | 3% |
| Other | 2 | 6% |
| Unknown | 13 | 36% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 14 | 39% |
| Business, Management and Accounting | 2 | 6% |
| Engineering | 2 | 6% |
| Agricultural and Biological Sciences | 1 | 3% |
| Medicine and Dentistry | 1 | 3% |
| Other | 1 | 3% |
| Unknown | 15 | 42% |
Attention Score in Context
This research output has an Altmetric Attention Score of 12. 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 05 March 2019.
All research outputs
#2,660,153
of 23,008,860 outputs
Outputs from Empirical Software Engineering
#51
of 707 outputs
Outputs of similar age
#53,634
of 330,017 outputs
Outputs of similar age from Empirical Software Engineering
#3
of 31 outputs
Altmetric has tracked 23,008,860 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 707 research outputs from this source. They receive a mean Attention Score of 4.8. This one has done particularly well, scoring higher than 92% 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 330,017 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 83% of its contemporaries.
We're also able to compare this research output to 31 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 90% of its contemporaries.