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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Computerarrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
Computer
Article . 1999 . Peer-reviewed
License: IEEE Copyright
Data sources: Crossref
DBLP
Article . 2020
Data sources: DBLP
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Albert Einstein and empirical software engineering

Authors: Shari Lawrence Pfleeger;

Albert Einstein and empirical software engineering

Abstract

The author believes that scientists apply scientific investigative techniques to gain more understanding of what makes software "good" and how to make software well. Often, they adapt investigative techniques from other disciplines to define measures that make sense in the business, technical, and social contexts people use for decision making. However, the author believes that sometimes failure can educate as well as success. Examples from nineteenth-century physics show how a change in perspective can lead to explanations for previously misunderstood phenomena. The author claims that scientists must also consider whether their measurements constrict their view of what is really happening in the development process, and they must change or expand the approach if they are. Science clearly illustrates the limitations of an overly literal approach to building and maintaining software. Too often, the author believes, scientists tend to view software development the same way nineteenth-century physicists viewed the universe. Taking a cue from Einstein, scientists should shape their theories and models to fit a more probabilistic reality.

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    36
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
36
Top 10%
Top 10%
Average
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