diff --git a/R/boxplot.R b/R/boxplot.R
index dbad99d..23f9229 100644
--- a/R/boxplot.R
+++ b/R/boxplot.R
@@ -1,80 +1,83 @@
 #' Creates dot- and boxplots
 #'
 #' Creates dot- and boxplots visualizing the assessment data separately for each algorithm.
 #' Boxplots representing descriptive statistics for all test cases (median, quartiles and outliers)
 #' are combined with horizontally jittered dots representing individual test cases.
 #'
 #' @param x The ranked assessment data set.
 #' @param color A string specifying the color of the dots.
 #' @param jitter.width A numeric value specifying the jitter width of the dots.
 #' @param ... Further arguments passed to or from other functions.
 #'
 #' @return
 #'
 #' @examples
 #'
 #' @seealso `browseVignettes("challengeR")`
 #'
 #' @family functions to visualize assessment data
 #' @export
 boxplot.ranked.list=function(x,
-                             color="blue",
                              jitter.width=0.25,...){
   algo=attr(x$data,"algorithm")
   value=attr(x$data,"value")
   ranking=x
   x=x$data
 
   for (i in names(x)) {
     x[[i]][[algo]]=factor(x[[i]][[algo]],
                           levels=rownames(ranking$matlist[[i]][order(ranking$matlist[[i]]$rank),]))
   }
 
   a=lapply(1:length(x),function(id){
-    ggplot(aes_string(algo,value),data=x[[id]])+
-      geom_jitter(position=position_jitter(width=jitter.width, height=0),
-                  color=color,...)+
-      geom_boxplot(outlier.shape = NA,fill=NA)+
+    ggplot(data=x[[id]])+
+      geom_jitter(aes_string(algo,value,color=algo),
+                  position=position_jitter(width=jitter.width, height=0),
+                  ...)+
+      geom_boxplot(aes_string(algo,value),
+                   outlier.shape = NA,fill=NA)+
       ggtitle(names(x)[id]) +
-      theme(axis.text.x=element_text(angle = -90, hjust = 0)) +
+      theme(axis.text.x=element_text(angle = -90, hjust = 0),
+            legend.position="none") +
       xlab("Algorithm") +
-      ylab("Metric value")
+      ylab("Metric value") 
   })
 
   # Remove title for single-task data set
   if (length(a) == 1) {
     a[[1]]$labels$title <- NULL
+    return(a[[1]])
   } else {
     names(a) = names(x$matlist)
-  }
-  class(a) <- "ggList"
-  a
+    class(a) <- "ggList"
+    return(a)
+ }
 }
 
 boxplot.comparedRanks.list=function(x,...){
   tau=sapply(x,function(z) z$tau)
   boxplot(tau,ylim=c(0,1.0),las=2, outline=FALSE,
           ylab="Kendall's tau",...)
   stripchart(tau,
              vertical = TRUE, method = "jitter",
              pch = 21, col = "blue", add=TRUE,...)
 
 }
 
 boxplot.bootstrap.list=function(x,...){
   winner.noboot=winner.ranked.list(x)
   x2=winnerFrequencies(x)
   n.bootstraps= ncol(x$bootsrappedRanks[[1]])
   perc_boot_Winner=lapply(1:length(x2),function(i){
     x2.i=x2[[i]]
     winner.id=which(rownames(x2.i)%in%rownames(winner.noboot[[i]])) #could be multiple winners!!!!
     100*x2.i[winner.id,3,drop=F]/n.bootstraps
   })
 
   boxplot(unlist(perc_boot_Winner),ylim=c(0,100),las=2, outline=FALSE,
           ylab="% Bootstraps",xlab="Winner ranks 1",
           sub=paste(n.bootstraps,"Bootstraps"),...)
   stripchart(unlist(perc_boot_Winner),
              vertical = TRUE, method = "jitter",
              pch = 21, col = "blue", add=TRUE,...)
 }