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#

# AssessEffectCodeOb.R, 16 Jul 18

#

# Data from:

# A Family of Experiments to Assess the Effectiveness and Efficiency of Source Code Obfuscation Techniques

# Mariano Ceccato and Massimiliano {Di Penta} and Paolo Falcarin and Filippo Ricca and Marco Torchiano and Paolo Tonella

#

# Example from:

# Empirical Software Engineering using R

# Derek M. Jones

#

# TAG experiment_human student_subjects source-code identifier control-flow

source("ESEUR_config.r")

library("car")

library("lme4")

# Exp,ID,Level,Average,Ability,Lab,Treatment,Application,Time1,Accuracy1,Time2,Accuracy2,Time3,Accuracy3,Time4,Accuracy4,Eff_Comp,Eff_Change,Eff_All

codeob=read.csv(paste0(ESEUR_dir, "sourcecode/AssessEffectCodeOb.csv.xz"), as.is=TRUE)

# table(codeob$Level, codeob$Treatment)

# Data cleaning

codeob$Average[13:14]=30

# codeob$Average=NULL

# bachelors did not do any 'clear' tests, i.e., no controls

codeob=subset(codeob, Level != "bachelor")

# T1_codeob=na.omit(codeob[ , 1:10])

T1_codeob=subset(codeob, !is.na(Time1))

T1_codeob$Average=as.numeric(T1_codeob$Average)

pairs(~ Time1 + Average, data=T1_codeob)

#gan_mod=lmer(Time1 ~ Level+(Ability+Lab+Treatment+Application)^2

gan_mod_1=lmer(Time1 ~ Treatment

+(1 | ID),

data=T1_codeob)

Anova(gan_mod_1)

summary(gan_mod_1)

# glm_mod=glmer(Accuracy1 ~ Level+(Ability+Lab+Treatment+Application)^2

glm_mod_1=glmer(Accuracy1 ~ Treatment

+(1 | ID),

data=T1_codeob, family=binomial)

Anova(glm_mod_1)

summary(glm_mod_1)

T2_codeob=subset(codeob, !is.na(Time2))

# T2_codeob=na.omit(codeob[ , 1:12])

# gan_mod=lmer(Time1 ~ Level+(Ability+Lab+Treatment+Application)^2

gan_mod_2=lmer(Time2 ~ Level+Treatment+Application

+(1 | ID),

data=T2_codeob)

Anova(gan_mod_2)

summary(gan_mod_2)

glm_mod_2=glmer(Accuracy2 ~ Level+Treatment+Application

+(1 | ID),

data=T2_codeob, family=binomial)

Anova(glm_mod_2)

T3_codeob=subset(codeob, !is.na(Time3))

# T3_codeob=na.omit(codeob[ , 1:14])

gan_mod_3=lmer(Time3 ~ Level+Treatment

+(1 | ID),

data=T3_codeob)

Anova(gan_mod_3)

summary(gan_mod_3)

T4_codeob=na.omit(codeob[ , 1:16])

gan_mod_4=lmer(Time4 ~ Level+Treatment+Application

+(1 | ID),

data=T4_codeob)

Anova(gan_mod_4)

summary(gan_mod_4)