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Erschienen in: Software and Systems Modeling 4/2017

07.09.2015 | Regular Paper

From software extensions to product lines of dataflow programs

verfasst von: Rui C. Gonçalves, Don Batory, João L. Sobral, Taylor L. Riché

Erschienen in: Software and Systems Modeling | Ausgabe 4/2017

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Abstract

Dataflow programs are widely used. Each program is a directed graph where nodes are computations and edges indicate the flow of data. In prior work, we reverse-engineered legacy dataflow programs by deriving their optimized implementations from a simple specification graph using graph transformations called refinements and optimizations. In MDE speak, our derivations were PIM-to-PSM mappings. In this paper, we show how extensions complement refinements, optimizations, and PIM-to-PSM derivations to make the process of reverse engineering complex legacy dataflow programs tractable. We explain how optional functionality in transformations can be encoded, thereby enabling us to encode product lines of transformations as well as product lines of dataflow programs. We describe the implementation of extensions in the \(\mathtt{ReFlO}\) tool and present two non-trivial case studies as evidence of our work’s generality.

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Fußnoten
1
In object-oriented parlance, \(\mathtt{E}\) is an extension of \(\mathtt{C}\) iff \(\mathtt{E}\) is a subclass of \(\mathtt{C}\).
 
2
In standard function composition notation, the order in which the transformations are listed is the reverse of the order in which they are applied.
 
3
Rule extensions need not be unique. Our experience to-date is that they are, largely because the increments in DfP functionality are sufficiently small for unique extensions to present themselves.
 
4
We can “relax” the correctness criteria of the simulation (and therefore change the behavior of the program) [57] to improve performance.
 
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Metadaten
Titel
From software extensions to product lines of dataflow programs
verfasst von
Rui C. Gonçalves
Don Batory
João L. Sobral
Taylor L. Riché
Publikationsdatum
07.09.2015
Verlag
Springer Berlin Heidelberg
Erschienen in
Software and Systems Modeling / Ausgabe 4/2017
Print ISSN: 1619-1366
Elektronische ISSN: 1619-1374
DOI
https://doi.org/10.1007/s10270-015-0495-8

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