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Verified Software: Theories, Tools, and Experiments

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Attention for Chapter 12: AUSPICE: Automatic Safety Property Verification for Unmodified Executables
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1 X user

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3 Mendeley
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Chapter title
AUSPICE: Automatic Safety Property Verification for Unmodified Executables
Chapter number 12
Book title
Verified Software: Theories, Tools, and Experiments
Published in
Lecture notes in computer science, January 2016
DOI 10.1007/978-3-319-29613-5_12
Book ISBNs
978-3-31-929612-8, 978-3-31-929613-5
Authors

Jiaqi Tan, Hui Jun Tay, Rajeev Gandhi, Priya Narasimhan, Tan, Jiaqi, Tay, Hui Jun, Gandhi, Rajeev, Narasimhan, Priya

Editors

Arie Gurfinkel, Sanjit A. Seshia

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 3 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 3 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 1 33%
Student > Master 1 33%
Unknown 1 33%
Readers by discipline Count As %
Computer Science 2 67%
Unknown 1 33%
Attention Score in Context

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 03 March 2016.
All research outputs
#15,362,070
of 22,852,911 outputs
Outputs from Lecture notes in computer science
#4,648
of 8,127 outputs
Outputs of similar age
#230,895
of 393,603 outputs
Outputs of similar age from Lecture notes in computer science
#382
of 581 outputs
Altmetric has tracked 22,852,911 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 8,127 research outputs from this source. They receive a mean Attention Score of 5.0. This one is in the 27th percentile – i.e., 27% 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 393,603 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 32nd percentile – i.e., 32% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 581 others from the same source and published within six weeks on either side of this one. This one is in the 24th percentile – i.e., 24% of its contemporaries scored the same or lower than it.