Permalink
Cannot retrieve contributors at this time
| # | |
| # 82507128-kitchenham.R, 18 Sep 20 | |
| # Data from: | |
| # An empirical study of maintenance and development estimation accuracy | |
| # Barbara Kitchenham and Shari Lawrence Pfleeger and Beth McColl and Suzanne Eagan | |
| # Magne J{\o}rgensen | |
| # Regression Models of Software Development Effort Estimation Accuracy and Bias | |
| # | |
| # Example from: | |
| # Evidence-based Software Engineering: based on the publicly available data | |
| # Derek M. Jones | |
| # | |
| # TAG effort_estimate effort_actual estimate_accuracy | |
| source("ESEUR_config.r") | |
| library("foreign") | |
| par(mar=MAR_default+c(0.0, 0.7, 0, 0)) | |
| pal_col=rainbow(3) | |
| kitch=read.arff(paste0(ESEUR_dir, "projects/82507128-kitchenham.arff")) | |
| jorg=read.csv(paste0(ESEUR_dir, "projects/Regression-models.csv.xz"), as.is=TRUE) | |
| plot(kitch$First.estimate, kitch$Actual.effort, log="xy", col=pal_col[1], | |
| xlim=c(5, max(kitch$First.estimate)), | |
| ylim=c(5, max(kitch$Actual.effort)), | |
| xlab="Estimate (hours)", ylab="Actual (hours)\n\n") | |
| points(jorg$Estimated.effort, jorg$Actual.effort, col=pal_col[3]) | |
| lines(c(5, 1e5), c(5, 1e5), col=pal_col[2]) | |
| legend(x="bottomright", legend=c("Kitchenham", "Jørgensen"), bty="n", fill=pal_col[-2], cex=1.2) | |
| x_bounds=exp(seq(1, log(max(kitch$First.estimate)), by=0.5)) | |
| j_mod=glm(log(Actual.effort) ~ log(Estimated.effort), data=jorg) | |
| summary(j_mod) | |
| pred=predict(j_mod, newdata=data.frame(Estimated.effort=x_bounds)) | |
| lines(x_bounds, exp(pred), col=pal_col[3]) | |
| k_mod=glm(log(Actual.effort) ~ log(First.estimate), data=kitch) | |
| summary(k_mod) | |
| pred=predict(k_mod, newdata=data.frame(First.estimate=x_bounds)) | |
| lines(x_bounds, exp(pred), col=pal_col[1]) | |
| # | |
| # plot(kitch$First.estimate, kitch$Adjusted.function.points, log="xy", col=point_col, | |
| # xlab="Estimate", ylab="Adjusted.function.points\n") | |
| # | |
| # plot(kitch$Actual.effort, kitch$Adjusted.function.points, log="xy", col=point_col, | |
| # xlab="Actual", ylab="Function points\n") | |
| # | |
| # library("MASS") | |
| # | |
| # e_mod=glm(Actual.effort ~ (First.estimate+Adjusted.function.points | |
| # +Client.code+Project.type | |
| # +First.estimate.method)^2 | |
| # , data=kitch) | |
| # | |
| # t=stepAIC(e_mod) | |
| # summary(t) | |
| # | |
| # | |
| # e_mod=glm(formula = Actual.effort ~ First.estimate | |
| # + First.estimate:Adjusted.function.points | |
| # + First.estimate:Client.code | |
| # , data = kitch) | |
| # | |
| # summary(e_mod) | |