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doi: 10.3850/978-3-9815370-4-8_0877
NFRs Early Estimation Through Software Metrics
Andrws Vieiraa, Pedro Faustinib, Luigi Carroc and Érika Cotad
PPGC - Informatics Institute - Federal University of Rio Grande do Sul (UFRGS), Porto Alegre, Brazil.
aandrwsvieira@inf.ufrgs.br
bphafaustini@inf.ufrgs.br
ccarro@inf.ufrgs.br
derika@inf.ufrgs.br
ABSTRACT
We propose the use of regression analysis to generate accurate predictive models for physical metrics using design metrics as input. We validate our approach with 40+ implementations of three systems in two development scenarios: system evolution and first design. Results show maximum prediction errors of 1.66% during system evolution. In a first design scenario, the average error is 15% with the maximum error still below 20% for all physical metrics. This approach provides a fast and accurate strategy to boost embedded software productivity and quality, by estimating Non-Functional Requirements (NFRs) during the first design stages.
Keywords: Embedded systems, Performance estimation, Software metrics, Regression analysis.
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