Title |
How effective are mutation testing tools? An empirical analysis of Java mutation testing tools with manual analysis and real faults
|
---|---|
Published in |
Empirical Software Engineering, December 2017
|
DOI | 10.1007/s10664-017-9582-5 |
Authors |
Marinos Kintis, Mike Papadakis, Andreas Papadopoulos, Evangelos Valvis, Nicos Malevris, Yves Le Traon |
X Demographics
The data shown below were collected from the profiles of 9 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 | 2 | 22% |
Italy | 1 | 11% |
India | 1 | 11% |
Sweden | 1 | 11% |
Brazil | 1 | 11% |
Netherlands | 1 | 11% |
Luxembourg | 1 | 11% |
Unknown | 1 | 11% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 7 | 78% |
Science communicators (journalists, bloggers, editors) | 1 | 11% |
Members of the public | 1 | 11% |
Mendeley readers
The data shown below were compiled from readership statistics for 63 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 63 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Master | 11 | 17% |
Student > Ph. D. Student | 9 | 14% |
Researcher | 5 | 8% |
Student > Doctoral Student | 5 | 8% |
Student > Bachelor | 5 | 8% |
Other | 12 | 19% |
Unknown | 16 | 25% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 36 | 57% |
Engineering | 8 | 13% |
Environmental Science | 1 | 2% |
Arts and Humanities | 1 | 2% |
Biochemistry, Genetics and Molecular Biology | 1 | 2% |
Other | 1 | 2% |
Unknown | 15 | 24% |
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 03 May 2019.
All research outputs
#5,611,465
of 23,577,654 outputs
Outputs from Empirical Software Engineering
#125
of 720 outputs
Outputs of similar age
#107,511
of 443,469 outputs
Outputs of similar age from Empirical Software Engineering
#9
of 28 outputs
Altmetric has tracked 23,577,654 research outputs across all sources so far. Compared to these this one has done well and is in the 76th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 720 research outputs from this source. They receive a mean Attention Score of 4.8. This one has done well, scoring higher than 82% 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 443,469 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 75% of its contemporaries.
We're also able to compare this research output to 28 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 67% of its contemporaries.