| Title |
A robust multi-objective approach to balance severity and importance of refactoring opportunities
|
|---|---|
| Published in |
Empirical Software Engineering, March 2016
|
| DOI | 10.1007/s10664-016-9426-8 |
| Authors |
Mohamed Wiem Mkaouer, Marouane Kessentini, Mel Ó Cinnéide, Shinpei Hayashi, Kalyanmoy Deb |
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 % |
|---|---|---|
| United States | 1 | 33% |
| Sweden | 1 | 33% |
| Unknown | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 2 | 67% |
| Science communicators (journalists, bloggers, editors) | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 65 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 65 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 17 | 26% |
| Student > Ph. D. Student | 10 | 15% |
| Student > Bachelor | 6 | 9% |
| Professor > Associate Professor | 6 | 9% |
| Student > Postgraduate | 4 | 6% |
| Other | 10 | 15% |
| Unknown | 12 | 18% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 41 | 63% |
| Engineering | 8 | 12% |
| Social Sciences | 2 | 3% |
| Chemical Engineering | 1 | 2% |
| Arts and Humanities | 1 | 2% |
| Other | 0 | 0% |
| Unknown | 12 | 18% |
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 17 June 2017.
All research outputs
#13,975,135
of 22,862,742 outputs
Outputs from Empirical Software Engineering
#427
of 705 outputs
Outputs of similar age
#151,835
of 298,950 outputs
Outputs of similar age from Empirical Software Engineering
#4
of 9 outputs
Altmetric has tracked 22,862,742 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 705 research outputs from this source. They receive a mean Attention Score of 4.8. This one is in the 37th percentile – i.e., 37% 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 298,950 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 9 others from the same source and published within six weeks on either side of this one. This one has scored higher than 5 of them.