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| # | |
| # icse14-sc_bc.R, 21 Feb 18 | |
| # | |
| # Data from: | |
| # Code Coverage for Suite Evaluation by Developers | |
| # Rahul Gopinath and Carlos Jensen and Alex Groce | |
| # | |
| # Example from: | |
| # Empirical Software Engineering using R | |
| # Derek M. Jones | |
| source("ESEUR_config.r") | |
| library("betareg") | |
| # plot_wide() | |
| load(paste0(ESEUR_dir, "reliability/o.db.rda")) | |
| cov_info=subset(o.db, loc > 0) | |
| cov_info$log_loc=log(cov_info$loc) | |
| cov_info$line_cov=cov_info$cobertura.line.num/cov_info$cobertura.line.total | |
| cov_info$branch_cov=cov_info$cobertura.branch.num/cov_info$cobertura.branch.total | |
| cov_info$block_cov=cov_info$nemma.block.num/cov_info$nemma.block.total | |
| cov_info$path_cov=cov_info$mockit.path.num/cov_info$mockit.path.total | |
| cov_info$mut_cov=cov_info$pit.mutation.num/cov_info$pit.mutation.total | |
| # Adjust range so values are just inside (0,1), for beta regression to work | |
| cov_info$line_cov=(cov_info$line_cov+1e-6)*0.999999 | |
| cov_info$mut_cov=(cov_info$mut_cov+1e-6)*0.999999 | |
| cov_info$path_cov=(cov_info$path_cov+1e-6)*0.999999 | |
| cov_info$branch_cov=(cov_info$branch_cov+1e-6)*0.999999 | |
| max_loc=max(cov_info$log_loc) | |
| mut_coverage=function(x_measure, y_measure, x_str, y_str, legend_pos) | |
| { | |
| applic=(y_measure > 0) & !(is.na(x_measure) | is.na(y_measure)) | |
| x_measure=x_measure[applic] | |
| y_measure=y_measure[applic] | |
| log_loc=subset(cov_info, applic)$log_loc | |
| plot(x_measure, y_measure, type="n", | |
| xlab=x_str, ylab=paste0(y_str, "\n")) | |
| pal_col=rainbow(1+max_loc) | |
| symbols(x_measure, y_measure, circles=log_loc, | |
| inches=1/15, add=T, fg=pal_col[log_loc+1]) | |
| # lines(loess.smooth(x_measure, y_measure, span=0.3), col="black") | |
| mc_mod=betareg(y_measure ~ (x_measure+log_loc)^2) | |
| # summary(mc_mod) | |
| pred=predict(mc_mod, newdata=data.frame(x_measure=x_bounds, log_loc=log(10^2))) | |
| lines(x_bounds, pred, col=pal_col[1+4]) | |
| pred=predict(mc_mod, newdata=data.frame(x_measure=x_bounds, log_loc=log(10^3))) | |
| lines(x_bounds, pred, col=pal_col[1+6]) | |
| pred=predict(mc_mod, newdata=data.frame(x_measure=x_bounds, log_loc=log(10^4))) | |
| lines(x_bounds, pred, col=pal_col[1+8]) | |
| legend(legend_pos, | |
| c(expression(LOC %~~% 10^2), expression(LOC %~~% 10^3), expression(LOC %~~% 10^4)), | |
| pch=21, bty='n', | |
| pt.cex=c(0.5, 1.0, 1.7), | |
| col=c(pal_col[1+4], pal_col[1+6], pal_col[1+8])) | |
| return(mc_mod) | |
| } | |
| x_bounds=seq(0.01, 0.99, by=0.01) | |
| # lp_mod=mut_coverage(cov_info$line_cov, cov_info$path_cov, | |
| # "Statement coverage", "Path coverage", "topleft") | |
| # mut_coverage(cov_info$line_cov, cov_info$block_cov, | |
| # "Statement coverage", "Block coverage", "topleft") | |
| lb_mod=mut_coverage(cov_info$line_cov, cov_info$branch_cov, | |
| "Statement coverage", "Branch coverage", "topleft") | |
| lines(c(0, 1), c(0, 1), col="grey") | |
| # plot(cov_info$log_loc, cov_info$line_cov, | |
| # xlab="log(LOC)", ylab="Statement coverage") | |
| # lines(loess.smooth(cov_info$log_loc, cov_info$line_cov, span=0.3), col="black") | |
| # loc_mod=betareg(line_cov ~ log_loc, data=cov_info) | |
| # summary(loc_mod) | |