Skip to main content

A Framework for Automatic Generation of Processes for Self-Adaptive Software Systems

da Silva, Carlos Eduardo, de Lemos, Rogério (2011) A Framework for Automatic Generation of Processes for Self-Adaptive Software Systems. Informatica, 35 (1). pp. 3-13. ISSN 0350-5596. (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:31875)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided.
Official URL:
http://www.informatica.si/PDF/35-1/02_daSilva%20-%...

Abstract

The self-adaptation of software systems is a complex process that depends on several factors that can change during the system operational lifetime. Hence, it is necessary to define mechanisms for providing a self-adaptive system the capability of generating during run-time the process that controls its adaptation. This paper presents a framework for the automatic generation of processes for self-adaptive software systems based on the use of workflows, model-based and artificial intelligence planning techniques. Our approach can be applied to different application domains, improves the scalability associated with the generation of adaptation plans, and enables the usage of different planning techniques. For evaluating the approach, we have developed a prototype for generating during run-time the workflows that coordinate the architectural reconfiguration of a web-based application.

Item Type: Article
Uncontrolled keywords: Architectural reconfiguration; Planning; Process; Self-adaptive systems; Workflow generation
Subjects: Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming, > QA76.76 Computer software
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
Depositing User: Rogerio de Lemos
Date Deposited: 23 Oct 2012 23:01 UTC
Last Modified: 16 Nov 2021 10:09 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/31875 (The current URI for this page, for reference purposes)

University of Kent Author Information

  • Depositors only (login required):

Total unique views for this document in KAR since July 2020. For more details click on the image.