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IEEE Software
Article . 2017 . Peer-reviewed
License: IEEE Copyright
Data sources: Crossref
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Context-Aware Software Variability through Adaptable Interpreters

Authors: W. Cazzola; A. Shaqiri;

Context-Aware Software Variability through Adaptable Interpreters

Abstract

Dynamic adaptation to the execution context is desirable in software that operates in an evolving environment. Context-oriented programming (COP) languages address behavioral variability from the programming-language perspective. COP has proven to be a valid approach when software is developed from scratch. However, it might require invasive, error-prone modifications when contextual variability is introduced to existing software written in non-COP languages, especially when variability is implicit in language constructs. A proposed approach moves variability support from the language to the language implementation level. This enables contextual variability in any application independently of whether the underlying language supports COP. A Neverlang-based prototype implementation illustrates this approach.

Related Organizations
Keywords

Context-Oriented Programming; Domain Specific Languages; Programming Languages; Dynamic Software Updatingl Software Evolution

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    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.
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    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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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!
4
Average
Average
Average
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