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Predicting software defects in varying development lifecycles using Bayesian nets

Overview of attention for article published in Information & Software Technology, January 2007
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wikipedia
1 Wikipedia page

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mendeley
156 Mendeley
citeulike
3 CiteULike
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Article details
Title
Predicting software defects in varying development lifecycles using Bayesian nets
Published in
Information & Software Technology, January 2007
DOI 10.1016/j.infsof.2006.09.001
Authors

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Timeline Attention over time Attention Score history
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Activity
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Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 156 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
United Kingdom 3 2%
Brazil 2 1%
United States 1 <1%
Turkey 1 <1%
Sweden 1 <1%
Russia 1 <1%
Portugal 1 <1%
Indonesia 1 <1%
Spain 1 <1%
Other 0 0%
Unknown 144 92%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Master 44 28%
Student > Ph. D. Student 30 19%
Researcher 22 14%
Student > Doctoral Student 7 4%
Lecturer 6 4%
Other 26 17%
Unknown 21 13%
Readers by discipline
Readers by discipline Count As %
Computer Science 95 61%
Engineering 20 13%
Business, Management and Accounting 3 2%
Psychology 2 1%
Social Sciences 2 1%
Other 8 5%
Unknown 26 17%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 21 December 2022.
All research outputs
#12,374,524
of 34,457,357 outputs
Outputs from Information & Software Technology
#479
of 1,986 outputs
Outputs of similar age
#73,238
of 228,217 outputs
Outputs of similar age from Information & Software Technology
#3
of 5 outputs
Altmetric has tracked 34,457,357 research outputs across all sources so far. This one is in the 38th percentile – i.e., 38% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,986 research outputs from this source. They receive a mean Attention Score of 2.8. This one has gotten more attention than average, scoring higher than 63% 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 228,217 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 12th percentile – i.e., 12% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 5 others from the same source and published within six weeks on either side of this one. This one has scored higher than 2 of them.