| Title |
Redundancy-free analysis of multi-revision software artifacts
|
|---|---|
| Published in |
Empirical Software Engineering, July 2018
|
| DOI | 10.1007/s10664-018-9630-9 |
| Authors |
Carol V. Alexandru, Sebastiano Panichella, Sebastian Proksch, Harald C. Gall |
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 % |
|---|---|---|
| Switzerland | 3 | 50% |
| Australia | 1 | 17% |
| Unknown | 2 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 3 | 50% |
| Members of the public | 2 | 33% |
| Science communicators (journalists, bloggers, editors) | 1 | 17% |
Mendeley readers
The data shown below were compiled from readership statistics for 34 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 34 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 6 | 18% |
| Student > Ph. D. Student | 5 | 15% |
| Student > Master | 4 | 12% |
| Student > Bachelor | 2 | 6% |
| Professor | 2 | 6% |
| Other | 5 | 15% |
| Unknown | 10 | 29% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 13 | 38% |
| Engineering | 5 | 15% |
| Business, Management and Accounting | 2 | 6% |
| Economics, Econometrics and Finance | 1 | 3% |
| Unknown | 13 | 38% |
Attention Score in Context
This research output has an Altmetric Attention Score of 6. 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 09 August 2019.
All research outputs
#5,799,091
of 23,098,660 outputs
Outputs from Empirical Software Engineering
#153
of 710 outputs
Outputs of similar age
#99,190
of 327,553 outputs
Outputs of similar age from Empirical Software Engineering
#5
of 17 outputs
Altmetric has tracked 23,098,660 research outputs across all sources so far. This one has received more attention than most of these and is in the 74th percentile.
So far Altmetric has tracked 710 research outputs from this source. They receive a mean Attention Score of 4.8. This one has done well, scoring higher than 78% 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 327,553 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 69% of its contemporaries.
We're also able to compare this research output to 17 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 70% of its contemporaries.