Filling the gap: a tool to automate parameter estimation for software performance models
Software performance engineering heavily relies on application and resource models that enable the prediction of Quality-of-Service metrics. Critical to these models is the accuracy of their parameters, the value of which can change with the application and the resources where it is deployed. In thi...
- Autores:
- Tipo de recurso:
- Fecha de publicación:
- 2015
- Institución:
- Universidad del Rosario
- Repositorio:
- Repositorio EdocUR - U. Rosario
- Idioma:
- eng
- OAI Identifier:
- oai:repository.urosario.edu.co:10336/28534
- Acceso en línea:
- https://doi.org/10.1145/2804371.2804379
https://repository.urosario.edu.co/handle/10336/28534
- Palabra clave:
- Software performance engineering
Quality of service
- Rights
- License
- Restringido (Acceso a grupos específicos)
| Summary: | Software performance engineering heavily relies on application and resource models that enable the prediction of Quality-of-Service metrics. Critical to these models is the accuracy of their parameters, the value of which can change with the application and the resources where it is deployed. In this paper we introduce the Filling-the-gap (FG) tool, which automates the parameter estimation of application performance models. This tool implements a set of statistical routines to estimate the parameters of performance models, which are automatically executed using monitoring information kept in a local database. |
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