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IEEE Transactions on Software Engineering
Article . 2016 . Peer-reviewed
License: IEEE Copyright
Data sources: Crossref
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A Two-Component Language for Adaptation: Design, Semantics and Program Analysis

Authors: DEGANO, PIERPAOLO; FERRARI, GIAN-LUIGI; GALLETTA, LETTERIO;

A Two-Component Language for Adaptation: Design, Semantics and Program Analysis

Abstract

Adaptive systems are designed to modify their behaviour in response to changes of their operational environment. We propose a two-component language for adaptive programming, within the Context-Oriented Programming paradigm. It has a declarative constituent for programming the context and a functional one for computing. We equip our language with a dynamic formal semantics. Since wrong adaptation could severely compromise the correct behaviour of applications and violate their properties, we also introduce a two-phase verification mechanism. It is based on a type and effect system that type-checks programs and computes, as an effect, a sound approximation of their behaviour. The effect is exploited at load time to mechanically verify that programs correctly adapt themselves to all possible running environments.

Related Organizations
Keywords

Adaptive software, context oriented programming, formal methods, datalog, functional programming, semantics, type systems, verification

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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!
10
Average
Top 10%
Top 10%
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