| Title |
An automated software reliability prediction system for safety critical software
|
|---|---|
| Published in |
Empirical Software Engineering, November 2015
|
| DOI | 10.1007/s10664-015-9412-6 |
| Authors |
Xiang Li, Chetan Mutha, Carol S. Smidts |
Mendeley readers
The data shown below were compiled from readership statistics for 15 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 15 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 4 | 27% |
| Student > Master | 3 | 20% |
| Researcher | 2 | 13% |
| Student > Doctoral Student | 1 | 7% |
| Professor > Associate Professor | 1 | 7% |
| Other | 0 | 0% |
| Unknown | 4 | 27% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 6 | 40% |
| Engineering | 5 | 33% |
| Unknown | 4 | 27% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 20 January 2017.
All research outputs
#20,390,619
of 22,940,083 outputs
Outputs from Empirical Software Engineering
#625
of 706 outputs
Outputs of similar age
#324,319
of 386,802 outputs
Outputs of similar age from Empirical Software Engineering
#2
of 12 outputs
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So far Altmetric has tracked 706 research outputs from this source. They receive a mean Attention Score of 4.8. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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We're also able to compare this research output to 12 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.