2015
DOI: 10.18293/seke2015-172
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An evolution management model for multi-level component-based software architectures

Abstract: Handling evolution in component-based software architectures is a non trivial task. Indeed, a series of changes applied on software may alter its architecture leading to several inconsistencies. In turn, architecture inconsistencies lead to software erosion and shorten its lifetime. To avoid architectural inconsistencies and increase software reliability, architecture evolution must be handled at all steps of the software lifecycle. Moreover, changes must be treated as first class entities. In this paper, we p… Show more

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Cited by 6 publications
(5 citation statements)
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References 17 publications
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“…Software Composition Analysis (SCA) [45], [46] refers to the process that provides visibility of open source components in a system. As stated by developer #14, "Managing a product against software decay can be a nightmare, but again a good SCA tool should be able to take care of that.…”
Section: ) Practicesmentioning
confidence: 99%
“…Software Composition Analysis (SCA) [45], [46] refers to the process that provides visibility of open source components in a system. As stated by developer #14, "Managing a product against software decay can be a nightmare, but again a good SCA tool should be able to take care of that.…”
Section: ) Practicesmentioning
confidence: 99%
“…An evolution plan aims at recovering consistence within architectural levels and coherence between those levels after a perturbation of any of the architecture levels. Also, the versioning activity has been considered in Dedal through a position paper, which presents a three-level versioning graph for managing Dedal architecture versioning [14].…”
Section: Previous Workmentioning
confidence: 99%
“…In previous work [19,20], we specified Dedal models using the B modeling language and proposed an evolution management model to enable the simulation, analysis and validation of evolution scenarios at any abstraction level using ProB. At that time, evolution was not yet automated since models were specified and evolved manually and separately.…”
Section: Motivation and Contributionmentioning
confidence: 99%
“…In previous work [20], we have made an evaluation of the performances of the ProB solver to generate evolution plans by state space exploration. The tested strategies were Depth-First (DF), Breadth-First (BF) and mixed (DF/BF) [23].…”
Section: The Dedalmanager Solvermentioning
confidence: 99%