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Software Engineering for Self-Adaptive Systems II

Overview of attention for book
Attention for Chapter 1: Software Engineering for Self-Adaptive Systems: A Second Research Roadmap
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (68th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (54th percentile)

Mentioned by

facebook
1 Facebook page
wikipedia
1 Wikipedia page

Citations

dimensions_citation
97 Dimensions

Readers on

mendeley
605 Mendeley
citeulike
2 CiteULike
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Chapter title
Software Engineering for Self-Adaptive Systems: A Second Research Roadmap
Chapter number 1
Book title
Software Engineering for Self-Adaptive Systems II
Published in
Lecture notes in computer science, January 2016
DOI 10.1007/978-3-642-35813-5_1
Book ISBNs
978-3-64-235812-8, 978-3-64-235813-5
Authors

de Lemos, Rogério, Giese, Holger, Müller, Hausi A., Shaw, Mary, Andersson, Jesper, Litoiu, Marin, Schmerl, Bradley, Tamura, Gabriel, Villegas, Norha M., Vogel, Thomas, Weyns, Danny, Baresi, Luciano, Becker, Basil, Bencomo, Nelly, Brun, Yuriy, Cukic, Bojan, Desmarais, Ron, Dustdar, Schahram, Engels, Gregor, Geihs, Kurt, Göschka, Karl M., Gorla, Alessandra, Grassi, Vincenzo, Inverardi, Paola, Karsai, Gabor, Kramer, Jeff, Lopes, Antónia, Magee, Jeff, Malek, Sam, Mankovskii, Serge, Mirandola, Raffaela, Mylopoulos, John, Nierstrasz, Oscar, Pezzè, Mauro, Prehofer, Christian, Schäfer, Wilhelm, Schlichting, Rick, Smith, Dennis B., Sousa, João Pedro, Tahvildari, Ladan, Wong, Kenny, Wuttke, Jochen, Rogério de Lemos, Holger Giese, Hausi A. Müller, Mary Shaw, Jesper Andersson, Marin Litoiu, Bradley Schmerl, Gabriel Tamura, Norha M. Villegas, Thomas Vogel, Danny Weyns, Luciano Baresi, Basil Becker, Nelly Bencomo, Yuriy Brun, Bojan Cukic, Ron Desmarais, Schahram Dustdar, Gregor Engels, Kurt Geihs, Karl M. Göschka, Alessandra Gorla, Vincenzo Grassi, Paola Inverardi, Gabor Karsai, Jeff Kramer, Antónia Lopes, Jeff Magee, Sam Malek, Serge Mankovskii, Raffaela Mirandola, John Mylopoulos, Oscar Nierstrasz, Mauro Pezzè, Christian Prehofer, Wilhelm Schäfer, Rick Schlichting, Dennis B. Smith, João Pedro Sousa, Ladan Tahvildari, Kenny Wong, Jochen Wuttke

Editors

Rogério de Lemos, Holger Giese, Hausi A. Müller, Mary Shaw

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 605 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
France 9 1%
Germany 9 1%
United Kingdom 8 1%
Brazil 7 1%
Spain 3 <1%
Portugal 3 <1%
Ireland 2 <1%
Italy 2 <1%
Indonesia 2 <1%
Other 19 3%
Unknown 541 89%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 197 33%
Student > Master 106 18%
Researcher 72 12%
Student > Doctoral Student 46 8%
Student > Bachelor 36 6%
Other 98 16%
Unknown 50 8%
Readers by discipline Count As %
Computer Science 450 74%
Engineering 52 9%
Business, Management and Accounting 8 1%
Social Sciences 7 1%
Chemistry 3 <1%
Other 19 3%
Unknown 66 11%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 23 June 2016.
All research outputs
#7,226,436
of 22,840,638 outputs
Outputs from Lecture notes in computer science
#2,400
of 8,127 outputs
Outputs of similar age
#119,310
of 395,188 outputs
Outputs of similar age from Lecture notes in computer science
#234
of 516 outputs
Altmetric has tracked 22,840,638 research outputs across all sources so far. This one has received more attention than most of these and is in the 67th percentile.
So far Altmetric has tracked 8,127 research outputs from this source. They receive a mean Attention Score of 5.0. This one has gotten more attention than average, scoring higher than 69% 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 395,188 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 68% of its contemporaries.
We're also able to compare this research output to 516 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 54% of its contemporaries.