Development and Instrumentation of a Framework for the Generation and Management of Self-Adaptive Enterprise Applications

Companies’ operations have become over-dependent on their supporting enterprise software applications. This situation has placed a heavy burden onto software maintenance teams who are expected to keep these applications up and running optimally in varying execution conditions. However, this high hum...

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Autores:
Tipo de recurso:
article
Fecha de publicación:
2016
Institución:
Pontificia Universidad Javeriana
Repositorio:
Repositorio Universidad Javeriana
Idioma:
eng
OAI Identifier:
oai:repository.javeriana.edu.co:10554/25788
Acceso en línea:
http://revistas.javeriana.edu.co/index.php/iyu/article/view/15215
http://hdl.handle.net/10554/25788
Palabra clave:
Rights
openAccess
License
Copyright (c) 2016 Hugo Arboleda, Andrés Paz, Miguel Jiménez, Gabriel Tamura
Description
Summary:Companies’ operations have become over-dependent on their supporting enterprise software applications. This situation has placed a heavy burden onto software maintenance teams who are expected to keep these applications up and running optimally in varying execution conditions. However, this high human intervention drives up the overall costs of software ownership. In addition, the current dynamic nature of enterprise applications constitutes challenges with respect to their architectural design and development, and the guarantee of the agreed quality requirements at runtime. Efficiently and effectively achieving the adaptation of enterprise applications requires an autonomic solution. In this paper we present SHIFT, a framework that provides (i) facilities and mechanisms for managing self-adaptive enterprise applications through the use of an autonomic infrastructure, and (ii) automated derivation of self-adaptive enterprise applications and their respective monitoring infrastructure. Along with the framework, our work leads us to propose a reference specification and architectural design for implementing self-adaptation autonomic infrastructures. We developed a reference implementation of SHIFT; our contribution includes the development of monitoring infrastructures, and dynamic adaptation planning and automated derivation strategies.