diff --git a/R/violin.R b/R/violin.R
index a62c6e0..e8c2968 100644
--- a/R/violin.R
+++ b/R/violin.R
@@ -1,81 +1,87 @@
 violin <- function(x,...) UseMethod("violin")
 violin.default <- function(x, ...) stop("not implemented for this class")
 
 violin.bootstrap=function(x,...){
   a=list(bootsrappedRanks=list(x$bootsrappedRanks),
          matlist=list(x$mat))
   names(a$bootsrappedRanks)=names(a$matlist)=""
   violin.bootstrap.list(a,...)
-  
+
 }
 
 
 violin.bootstrap.list=function(x,...){
   ken=melt(kendall.bootstrap.list(x))
   colnames(ken)[2]="Task"
   cat("\n\nSummary Kendall's tau\n")
   ss=ken%>%group_by(Task)%>%
     summarise(mean=mean(value,na.rm=T),
               median=median(value,na.rm=T),
               q25=quantile(value,probs = .25,na.rm=T),
-              q75=quantile(value,probs = .75,na.rm=T))%>% 
+              q75=quantile(value,probs = .75,na.rm=T))%>%
     arrange(desc(median))
-  
+
   print(as.data.frame(ss))
-  
-  ken%>%mutate(Task=factor(.data$Task, 
+
+  xAxisText <- element_blank()
+
+  # Show task names as tick mark labels only for multi-task data set
+  if (length(x$data) > 1) {
+    xAxisText <- element_text(angle = 90, vjust = 0.5, hjust = 1)
+  }
+
+  ken%>%mutate(Task=factor(.data$Task,
                            levels=ss$Task))%>%
     ggplot(aes(Task,value))+
     geom_violin(alpha=.3,
                 color=NA,
                 fill="blue")+
-    geom_boxplot(width=0.1, 
+    geom_boxplot(width=0.1,
                  fill="white")+
-    theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1),
+    theme(axis.text.x = xAxisText,
           legend.position = "none")+
     ylab("Kendall's tau")+
     scale_y_continuous(limits=c(min(min(ken$value),0),
                                 max(max(ken$value),1)))
 }
 
 
 
 kendall.bootstrap.list=function(x){
   ken=lapply(1:length(x$bootsrappedRanks),function(Task){
     id=match(rownames( x$bootsrappedRanks[[Task]]),
              rownames(x$matlist[[Task]]) )
-    sapply(x$bootsrappedRanks[[Task]], 
+    sapply(x$bootsrappedRanks[[Task]],
            function(bootSample) suppressWarnings(kendall(bootSample,
                                                          x$matlist[[Task]]$rank[id])))
   } )
   names(ken)=names((x$bootsrappedRanks))
-  
+
   if (sum(is.na(x))>0){
    cat("Bootstrap samples without variability in rankings (all algorithms ranked 1) excluded.\n Frequency of such samples by task:\n",fill = T)
     sapply(ken,function(x) sum(is.na(x)))
   }
-  
-  
+
+
   return(ken)
-  
+
 }
 
 
 density.bootstrap.list=function(x,...){
   ken=melt(kendall.bootstrap.list(x))
   colnames(ken)[2]="Task"
-  
+
   cat("\n\nSummary Kendall's tau\n")
   ss=ken%>%group_by(Task)%>%
     summarise(mean=mean(value,na.rm=T),
               median=median(value,na.rm=T),
               q25=quantile(value,probs = .25,na.rm=T),
-              q75=quantile(value,probs = .75,na.rm=T))%>% 
+              q75=quantile(value,probs = .75,na.rm=T))%>%
     arrange(desc(median))
-  
+
   print(as.data.frame(ss))
-  
+
   ggplot(ken)+
     geom_density(aes(value,fill=Task),alpha=.3,color=NA)
 }
-
diff --git a/tests/testthat/test-violinPlot.R b/tests/testthat/test-violinPlot.R
new file mode 100644
index 0000000..eee36f9
--- /dev/null
+++ b/tests/testthat/test-violinPlot.R
@@ -0,0 +1,52 @@
+test_that("violin plot for visualizing ranking stability returns one plot for single-task data set", {
+  data <- rbind(
+    data.frame(algo="A1", value=0.8, case="C1"),
+    data.frame(algo="A2", value=0.6, case="C1"),
+    data.frame(algo="A3", value=0.4, case="C1"),
+    data.frame(algo="A1", value=0.2, case="C2"),
+    data.frame(algo="A2", value=0.1, case="C2"),
+    data.frame(algo="A3", value=0.0, case="C2"))
+
+  challenge <- as.challenge(data, taskName="T1", algorithm="algo", case="case", value="value", smallBetter=FALSE)
+
+  ranking <- challenge%>%aggregateThenRank(FUN=median, ties.method="min")
+
+  set.seed(1)
+  rankingBootstrapped <- ranking%>%bootstrap(nboot=10)
+
+  actualPlot <- violin(rankingBootstrapped)
+  expect_is(actualPlot, "ggplot")
+})
+
+test_that("violin plot for visualizing ranking stability returns one plot for multi-task data set", {
+  dataTask1 <- cbind(task="T1",
+                     rbind(
+                       data.frame(algo="A1", value=0.8, case="C1"),
+                       data.frame(algo="A2", value=0.6, case="C1"),
+                       data.frame(algo="A3", value=0.4, case="C1"),
+                       data.frame(algo="A1", value=0.2, case="C2"),
+                       data.frame(algo="A2", value=0.1, case="C2"),
+                       data.frame(algo="A3", value=0.0, case="C2")
+                     ))
+  dataTask2 <- cbind(task="T2",
+                     rbind(
+                       data.frame(algo="A1", value=0.2, case="C1"),
+                       data.frame(algo="A2", value=0.3, case="C1"),
+                       data.frame(algo="A3", value=0.4, case="C1"),
+                       data.frame(algo="A1", value=0.7, case="C2"),
+                       data.frame(algo="A2", value=0.8, case="C2"),
+                       data.frame(algo="A3", value=0.9, case="C2")
+                     ))
+
+  data <- rbind(dataTask1, dataTask2)
+
+  challenge <- as.challenge(data, by="task", algorithm="algo", case="case", value="value", smallBetter=FALSE)
+
+  ranking <- challenge%>%aggregateThenRank(FUN=median, ties.method="min")
+
+  set.seed(1)
+  rankingBootstrapped <- ranking%>%bootstrap(nboot=10)
+
+  actualPlot <- violin(rankingBootstrapped)
+  expect_is(actualPlot, "ggplot")
+})