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Dynamic visualisation of features and contexts for context-oriented programmers

Authors: Duhoux, Benoît; Dumas, Bruno; Leung, Hoo Sing; Mens, Kim; EICS '19 Proceedings of the ACM SIGCHI Symposium on Engineering Interactive Computing Systems;

Dynamic visualisation of features and contexts for context-oriented programmers

Abstract

Context-oriented programming languages allow programmers to develop context-aware systems that can adapt their behaviour dynamically upon changing contexts. Due to the highly dynamic nature of such systems and the many possible combinations of contexts to which such systems may adapt, developing such systems is hard. Feature-based context-oriented programming helps tackle part of this complexity by modelling the possible contexts, and the different behavioural adaptations they can trigger, as separate feature models. Tools can also help developers address the underlying complexity of this approach. This paper presents a visualisation tool that is intricately related to the underlying architecture of a feature-based context-oriented programming language, and the context and feature models it uses. The visualisation confronts two hierarchical models (a context model and a feature model) and highlights the dependencies between them. An initial user study of the visualisation tool is performed to assess its usefulness and usability.

Keywords

Context-oriented programming, context-oriented programming, Feature-oriented software development, dynamic software adaptation, feature-oriented software development, Dynamic software adaptation, Software visualisation

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    influence
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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!
1
Average
Average
Average
Green