Characterizing a synthetic workload for performance evaluation during the migration of a legacy system

Silva, P.P. da; Laender, Alberto H. F.; Resende, Rodolfo F.; Golgher, Paulo B.

doi:10.1109/csmr.2000.827325

Cited by 4 publications

(2 citation statements)

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“…Since a given transaction in the legacy system may not directly have a corresponding transaction in the target system, services are used to establish a mapping for the purpose of identifying the corresponding transactions between the legacy and the target systems. Services are abstractions of their subtasks (i.e., transactions) where actions and user interactions occur [9].…”

Section: The Capples Methodsmentioning

confidence: 99%

“…To the best of our knowledge, CAPPLES 1 is the only method developed specifically for the performance evaluation of target systems during the migration of legacy systems (da Silva et al [7,8,9]). Although the methodology of CAPPLES has been shown to be effective in addressing several issues of performance evaluation during system migration, we believe that CAPPLES may suffer from several limitations (these are discussed in Section 2).…”

Section: Introductionmentioning

confidence: 99%

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Al-Azzoni¹,

Zhang²,

Down³

2011

SIGSOFT Softw. Eng. Notes

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Advances in technology and economical pressure have forced many organizations to consider the migration of their legacy systems to newer platforms. Legacy systems typically provide mission critical services vital for an organization's business needs. These systems are usually very large and highly complex with little or no documentation. Furthermore, fewer people can understand and maintain these systems. While several techniques exist to verify the functionality of the migrated system, the literature is still lacking methods to effectively assess the performance impact of software migration. In this paper, we propose a new method designed specifically to address performance evaluation in software migration projects. The new method uses simple models and incorporates techniques for model validation and resource demand mapping for performance evaluation and capacity planning.

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Section: The Capples Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%