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Modelling programming language semantics using a common semantic model

Authors: Huynh, Cong Phuoc;

Modelling programming language semantics using a common semantic model

Abstract

Software Engineers are interested in understanding software structure in order to manage its complexity, and to assure and improve its quality. Semantic models can inform tools to communicate this information to humans. The .NET framework provides a common semantic underpinning for a wide range of programming languages in an intermediate language. Nevertheless, there is a semantic gap between the intermediate language and specific programming languages. This research aims to model the mapping between the common semantic concepts and programming language specific concepts. The main benefit of the mapping is to allow us to define metrics, heuristics and visualizations on a set of common semantics and to compare them rigourously across various programming languages. We propose an architecture for mapping the semantics of multiple programming languages to .NET. In addition, we analyze and design a bidirectional mapping between Java and .NET as part of this architecture. The mapping model is implemented based on existing Java and .NET semantic models, and has been verified on a number of Java and .NET applications.

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New Zealand
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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!
0
Average
Average
Average
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