Title :
NFRs early estimation through software metrics
Author :
Vieira, Andrws ; Faustini, Pedro ; Carro, Luigi ; Cota, Erika
Author_Institution :
PPGC - Inf. Inst., Fed. Univ. of Rio Grande do Sul (UFRGS), Porto Alegre, Brazil
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 :
regression analysis; software metrics; software quality; NFR early estimation; design metrics; embedded software productivity; embedded software quality; maximum prediction errors; nonfunctional requirements; physical metrics; predictive models; regression analysis; software metrics; Automation; Decision support systems; Embedded systems; Estimation; Europe; Regression analysis; Software metrics; Embedded Systems; Performance Estimation; Regression Analysis; Software Metrics;
Conference_Titel :
Design, Automation & Test in Europe Conference & Exhibition (DATE), 2015
Conference_Location :
Grenoble
Print_ISBN :
978-3-9815-3704-8