| Title |
On the diffuseness and the impact on maintainability of code smells: a large scale empirical investigation
|
|---|---|
| Published in |
Empirical Software Engineering, August 2017
|
| DOI | 10.1007/s10664-017-9535-z |
| Authors |
Fabio Palomba, Gabriele Bavota, Massimiliano Di Penta, Fausto Fasano, Rocco Oliveto, Andrea De Lucia |
X Demographics
The data shown below were collected from the profiles of 7 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 | 14% |
| Netherlands | 1 | 14% |
| New Zealand | 1 | 14% |
| Sweden | 1 | 14% |
| Unknown | 3 | 43% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 5 | 71% |
| Scientists | 1 | 14% |
| Science communicators (journalists, bloggers, editors) | 1 | 14% |
Mendeley readers
The data shown below were compiled from readership statistics for 170 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 170 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 35 | 21% |
| Student > Ph. D. Student | 28 | 16% |
| Student > Bachelor | 19 | 11% |
| Researcher | 9 | 5% |
| Student > Doctoral Student | 8 | 5% |
| Other | 25 | 15% |
| Unknown | 46 | 27% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 96 | 56% |
| Engineering | 8 | 5% |
| Business, Management and Accounting | 3 | 2% |
| Unspecified | 2 | 1% |
| Nursing and Health Professions | 1 | <1% |
| Other | 4 | 2% |
| Unknown | 56 | 33% |
Attention Score in Context
This research output has an Altmetric Attention Score of 8. 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 06 June 2022.
All research outputs
#4,130,473
of 23,900,102 outputs
Outputs from Empirical Software Engineering
#89
of 733 outputs
Outputs of similar age
#70,261
of 319,993 outputs
Outputs of similar age from Empirical Software Engineering
#5
of 16 outputs
Altmetric has tracked 23,900,102 research outputs across all sources so far. Compared to these this one has done well and is in the 82nd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 733 research outputs from this source. They receive a mean Attention Score of 4.7. This one has done well, scoring higher than 87% 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 319,993 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 78% of its contemporaries.
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 has done well, scoring higher than 75% of its contemporaries.