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\begin{document}

\title{Higher-Order Transformation for Incremental Propagation of Changes from
Software to Performance Models}



\author[1]{Taghreed A. Altamimi}%
\author[2]{Dorina C. Petriu}%
\affil[1]{Alfaisal University College of Engineering}%
\affil[2]{Carleton University}%


\vspace{-1em}



  
  \date{May 15, 2024}


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\begin{abstract}
This paper proposes a higher-order transformation (HOT) for realizing
Incremental Change Propagation (ICP) from software UML models extended
with performance annotations to performance Layered Queueing Network
(LQN) models. Such a transformation is necessary for integrating
quantitative performance analysis into the model-driven engineering of
real-time systems. The entire process starts by automatically generating
an LQN and a trace model from a UML model extended with MARTE
annotations, with a batch Epsilon ETL transformation previously
developed by the authors. The textual ETL transformation definition is
translated to an ETL transformation model using the Epsilon Haetae tool.
The ETL transformation model conforms to the ETL metamodel and
represents the mapping between source and target models at a high level
of abstraction. We use it to answer the question: what needs to be
changed in the target model upon detecting changes in the source model?
During the development process, when the UML model evolves, we detect
such changes with the Eclipse EMF Compare tool, then incrementally
propagate them to the LQN model to keep it synchronized. The extended
approach is illustrated by applying it to an e-commerce model from the
literature. The execution time of ICP is measured and compared to the
traditional batch transformation.%
\end{abstract}%



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\textbf{Hosted file}

\verb`Higher-Order Transformation for ICP.docx`  available at \url{https://authorea.com/users/764146/articles/741827-higher-order-transformation-for-incremental-propagation-of-changes-from-software-to-performance-models}

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