diff --git a/tests/testthat/test-blobPlotStabilityByAlgorithm.R b/tests/testthat/test-blobPlotStabilityByAlgorithm.R
index 66d0ff6..392fe06 100644
--- a/tests/testthat/test-blobPlotStabilityByAlgorithm.R
+++ b/tests/testthat/test-blobPlotStabilityByAlgorithm.R
@@ -1,140 +1,207 @@
 # Copyright (c) German Cancer Research Center (DKFZ)
 # All rights reserved.
 #
 # This file is part of challengeR.
 #
 # challengeR is free software: you can redistribute it and/or modify
 # it under the terms of the GNU General Public License as published by
 # the Free Software Foundation, either version 2 of the License, or
 # (at your option) any later version.
 #
 # challengeR is distributed in the hope that it will be useful,
 # but WITHOUT ANY WARRANTY; without even the implied warranty of
 # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
 # GNU General Public License for more details.
 #
 # You should have received a copy of the GNU General Public License
 # along with challengeR. If not, see <https://www.gnu.org/licenses/>.
 
 test_that("blob plot for visualizing ranking stability by algorithm raises error 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)
 
   expect_error(stabilityByAlgorithm(rankingBootstrapped),
                "The stability of rankings by algorithm cannot be computed for less than two tasks.", fixed=TRUE)
 })
 
 test_that("blob plot for visualizing ranking stability by algorithm 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 <- stabilityByAlgorithm(rankingBootstrapped)
   expect_is(actualPlot, "ggplot")
 })
 
 test_that("blob plot for visualizing ranking stability by algorithm returns a plot for each algorithm", {
   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)
 
   meanRanks <- ranking%>%consensus(method = "euclidean")
 
   actualPlot <- stabilityByAlgorithm(rankingBootstrapped, ordering = names(meanRanks), single = TRUE)
   expect_equal(length(actualPlot), 3)
   expect_is(actualPlot[[1]], "ggplot")
   expect_is(actualPlot[[2]], "ggplot")
   expect_is(actualPlot[[3]], "ggplot")
 })
 
-
-
 test_that("Multi task bootstrapping, only one task with >1 test case stability plot works", {
   dataTask1 <- cbind(task="T1",
                      rbind(
                        data.frame(algo="A1", value=0.8, case="C1"),
                        data.frame(algo="A2", value=0.6, case="C1")
                      ))
   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="A1", value=0.2, case="C2"),
                        data.frame(algo="A2", value=0.3, case="C2")
                      ))
   dataTask3 <- cbind(task="T3",
                      rbind(
                        data.frame(algo="A1", value=0.1, case="C1"),
                        data.frame(algo="A2", value=0.8, case="C1")
                      ))
-  
+
   data <- rbind(dataTask1, dataTask2, dataTask3)
-  
+
   challenge <- as.challenge(data, by="task", algorithm="algo", case="case", value="value", smallBetter=FALSE)
-  
+
   ranking <- challenge%>%aggregateThenRank(FUN=median, ties.method="min")
   rankingBootstrapped <- ranking%>%bootstrap(nboot=3)
   meanRanks <- ranking%>%consensus(method = "euclidean")
   actualPlot <- stabilityByAlgorithm(rankingBootstrapped, ordering = names(meanRanks), single = FALSE)
   expect_is(actualPlot, "ggplot")
 })
+
+test_that("blob plot for visualizing ranking stability by algorithm returns one plot if #algorithms equals #tasks", {
+  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="A1", value=0.2, case="C2"),
+                       data.frame(algo="A2", value=0.1, 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="A1", value=0.7, case="C2"),
+                       data.frame(algo="A2", value=0.8, 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)
+
+  meanRanks <- ranking%>%consensus(method = "euclidean")
+
+  actualPlot <- stabilityByAlgorithm(rankingBootstrapped, ordering = names(meanRanks), single = FALSE)
+  expect_is(actualPlot, "ggplot")
+})
+
+test_that("blob plot for visualizing ranking stability by algorithm returns one plot if #algorithms < #tasks", {
+  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="A1", value=0.8, case="C2"),
+                       data.frame(algo="A2", value=0.6, 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="A1", value=0.2, case="C2"),
+                       data.frame(algo="A2", value=0.3, case="C2")
+                     ))
+  dataTask3 <- cbind(task="T3",
+                     rbind(
+                       data.frame(algo="A1", value=0.1, case="C1"),
+                       data.frame(algo="A2", value=0.8, case="C1"),
+                       data.frame(algo="A1", value=0.1, case="C2"),
+                       data.frame(algo="A2", value=0.8, case="C2")
+                     ))
+
+  data <- rbind(dataTask1, dataTask2, dataTask3)
+
+  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)
+
+  meanRanks <- ranking%>%consensus(method = "euclidean")
+
+  actualPlot <- stabilityByAlgorithm(rankingBootstrapped, ordering = names(meanRanks), single = FALSE)
+  expect_is(actualPlot, "ggplot")
+})
diff --git a/tests/testthat/test-report.R b/tests/testthat/test-report.R
index 54c0fbd..f911f0b 100644
--- a/tests/testthat/test-report.R
+++ b/tests/testthat/test-report.R
@@ -1,485 +1,536 @@
 # Copyright (c) German Cancer Research Center (DKFZ)
 # All rights reserved.
 #
 # This file is part of challengeR.
 #
 # challengeR is free software: you can redistribute it and/or modify
 # it under the terms of the GNU General Public License as published by
 # the Free Software Foundation, either version 2 of the License, or
 # (at your option) any later version.
 #
 # challengeR is distributed in the hope that it will be useful,
 # but WITHOUT ANY WARRANTY; without even the implied warranty of
 # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
 # GNU General Public License for more details.
 #
 # You should have received a copy of the GNU General Public License
 # along with challengeR. If not, see <https://www.gnu.org/licenses/>.
 
 test_that("PDF report for single-task data set without bootstrapping is created", {
   data <- rbind(
     data.frame(algo="A1", value=0.8, case="C1"),
     data.frame(algo="A2", value=0.6, case="C1"))
 
   challenge <- as.challenge(data, taskName="T1", algorithm="algo", case="case", value="value", smallBetter=FALSE)
 
   ranking <- challenge%>%aggregateThenRank(FUN=median, ties.method="min")
 
   ranking %>%
     report(title="Test Challenge",
            file="testthat_single_task_no_bootstrapping",
            format="PDF",
            clean=TRUE,
            open=FALSE)
 
   expect_true(file.exists("testthat_single_task_no_bootstrapping.pdf"))
 
   # Clean up
   if (file.exists("testthat_single_task_no_bootstrapping.pdf")) {
     file.remove("testthat_single_task_no_bootstrapping.pdf")
   }
 
 })
 
 test_that("HTML report for single-task data set without bootstrapping is created", {
   data <- rbind(
     data.frame(algo="A1", value=0.8, case="C1"),
     data.frame(algo="A2", value=0.6, case="C1"))
 
   challenge <- as.challenge(data, taskName="T1", algorithm="algo", case="case", value="value", smallBetter=FALSE)
 
   ranking <- challenge%>%aggregateThenRank(FUN=median, ties.method="min")
 
   ranking %>%
     report(title="Test Challenge",
            file="testthat_single_task_no_bootstrapping",
            format="HTML",
            clean=TRUE,
            open=FALSE)
 
   expect_true(file.exists("testthat_single_task_no_bootstrapping.html"))
 
   # Clean up
   if (file.exists("testthat_single_task_no_bootstrapping.html")) {
     file.remove("testthat_single_task_no_bootstrapping.html")
   }
 
 })
 
 test_that("Word report for single-task data set without bootstrapping is created", {
   data <- rbind(
     data.frame(algo="A1", value=0.8, case="C1"),
     data.frame(algo="A2", value=0.6, case="C1"))
 
   challenge <- as.challenge(data, taskName="T1", algorithm="algo", case="case", value="value", smallBetter=FALSE)
 
   ranking <- challenge%>%aggregateThenRank(FUN=median, ties.method="min")
 
   ranking %>%
     report(title="Test Challenge",
            file="testthat_single_task_no_bootstrapping",
            format="Word",
            clean=TRUE,
            open=FALSE)
 
   expect_true(file.exists("testthat_single_task_no_bootstrapping.docx"))
 
   # Clean up
   if (file.exists("testthat_single_task_no_bootstrapping.docx")) {
     file.remove("testthat_single_task_no_bootstrapping.docx")
   }
 
 })
 
 test_that("PDF report for single-task data set with bootstrapping is created", {
   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)
 
   rankingBootstrapped %>%
     report(title="Test Challenge",
            file="testthat_single_task_bootstrapping",
            format="PDF",
            clean=TRUE,
            open=FALSE)
 
   expect_true(file.exists("testthat_single_task_bootstrapping.pdf"))
 
   # Clean up
   if (file.exists("testthat_single_task_bootstrapping.pdf")) {
     file.remove("testthat_single_task_bootstrapping.pdf")
   }
 
 })
 
 test_that("HTML report for single-task data set with bootstrapping is created", {
   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)
 
   rankingBootstrapped %>%
     report(title="Test Challenge",
            file="testthat_single_task_bootstrapping",
            format="HTML",
            clean=TRUE,
            open=FALSE)
 
   expect_true(file.exists("testthat_single_task_bootstrapping.html"))
 
   # Clean up
   if (file.exists("testthat_single_task_bootstrapping.html")) {
     file.remove("testthat_single_task_bootstrapping.html")
   }
 
 })
 
 test_that("Word report for single-task data set with bootstrapping is created", {
   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)
 
   rankingBootstrapped %>%
     report(title="Test Challenge",
            file="testthat_single_task_bootstrapping",
            format="Word",
            clean=TRUE,
            open=FALSE)
 
   expect_true(file.exists("testthat_single_task_bootstrapping.docx"))
 
   # Clean up
   if (file.exists("testthat_single_task_bootstrapping.docx")) {
     file.remove("testthat_single_task_bootstrapping.docx")
   }
 
 })
 
 test_that("PDF report for multi-task data set without bootstrapping is created", {
   dataTask1 <- cbind(task="T1",
                      rbind(
                        data.frame(algo="A1", value=0.8, case="C1"),
                        data.frame(algo="A2", value=0.6, case="C1")
                      ))
   dataTask2 <- cbind(task="T2",
                      rbind(
                        data.frame(algo="A1", value=0.2, case="C1"),
                        data.frame(algo="A2", value=0.3, case="C1")
                      ))
   dataTask3 <- cbind(task="T3",
                      rbind(
                        data.frame(algo="A1", value=0.1, case="C1"),
                        data.frame(algo="A2", value=0.8, case="C1")
                      ))
 
   data <- rbind(dataTask1, dataTask2, dataTask3)
 
   challenge <- as.challenge(data, by="task", algorithm="algo", case="case", value="value", smallBetter=FALSE)
 
   ranking <- challenge%>%aggregateThenRank(FUN=median, ties.method="min")
 
   meanRanks <- ranking%>%consensus(method = "euclidean")
 
   ranking %>%
     report(consensus=meanRanks,
            title="Test Challenge",
            file="testthat_multi_task_no_bootstrapping",
            format="PDF",
            clean=TRUE,
            open=FALSE)
 
   expect_true(file.exists("testthat_multi_task_no_bootstrapping.pdf"))
 
   # Clean up
   if (file.exists("testthat_multi_task_no_bootstrapping.pdf")) {
     file.remove("testthat_multi_task_no_bootstrapping.pdf")
   }
 
 })
 
 test_that("HTML report for multi-task data set without bootstrapping is created", {
   dataTask1 <- cbind(task="T1",
                      rbind(
                        data.frame(algo="A1", value=0.8, case="C1"),
                        data.frame(algo="A2", value=0.6, case="C1")
                      ))
   dataTask2 <- cbind(task="T2",
                      rbind(
                        data.frame(algo="A1", value=0.2, case="C1"),
                        data.frame(algo="A2", value=0.3, case="C1")
                      ))
   dataTask3 <- cbind(task="T3",
                      rbind(
                        data.frame(algo="A1", value=0.1, case="C1"),
                        data.frame(algo="A2", value=0.8, case="C1")
                      ))
 
   data <- rbind(dataTask1, dataTask2, dataTask3)
 
   challenge <- as.challenge(data, by="task", algorithm="algo", case="case", value="value", smallBetter=FALSE)
 
   ranking <- challenge%>%aggregateThenRank(FUN=median, ties.method="min")
 
   meanRanks <- ranking%>%consensus(method = "euclidean")
 
   ranking %>%
     report(consensus=meanRanks,
            title="Test Challenge",
            file="testthat_multi_task_no_bootstrapping",
            format="HTML",
            clean=TRUE,
            open=FALSE)
 
   expect_true(file.exists("testthat_multi_task_no_bootstrapping.html"))
 
   # Clean up
   if (file.exists("testthat_multi_task_no_bootstrapping.html")) {
     file.remove("testthat_multi_task_no_bootstrapping.html")
   }
 
 })
 
 test_that("Word report for multi-task data set without bootstrapping is created", {
   dataTask1 <- cbind(task="T1",
                      rbind(
                        data.frame(algo="A1", value=0.8, case="C1"),
                        data.frame(algo="A2", value=0.6, case="C1")
                      ))
   dataTask2 <- cbind(task="T2",
                      rbind(
                        data.frame(algo="A1", value=0.2, case="C1"),
                        data.frame(algo="A2", value=0.3, case="C1")
                      ))
   dataTask3 <- cbind(task="T3",
                      rbind(
                        data.frame(algo="A1", value=0.1, case="C1"),
                        data.frame(algo="A2", value=0.8, case="C1")
                      ))
 
   data <- rbind(dataTask1, dataTask2, dataTask3)
 
   challenge <- as.challenge(data, by="task", algorithm="algo", case="case", value="value", smallBetter=FALSE)
 
   ranking <- challenge%>%aggregateThenRank(FUN=median, ties.method="min")
 
   meanRanks <- ranking%>%consensus(method = "euclidean")
 
   ranking %>%
     report(consensus=meanRanks,
            title="Test Challenge",
            file="testthat_multi_task_no_bootstrapping",
            format="Word",
            clean=TRUE,
            open=FALSE)
 
   expect_true(file.exists("testthat_multi_task_no_bootstrapping.docx"))
 
   # Clean up
   if (file.exists("testthat_multi_task_no_bootstrapping.docx")) {
     file.remove("testthat_multi_task_no_bootstrapping.docx")
   }
 
 })
 
 test_that("PDF report for multi-task data set with bootstrapping is created", {
   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")
                      ))
   dataTask3 <- cbind(task="T3",
                      rbind(
                        data.frame(algo="A1", value=0.1, case="C1"),
                        data.frame(algo="A2", value=0.2, case="C1"),
                        data.frame(algo="A3", value=0.3, case="C1"),
                        data.frame(algo="A1", value=0.6, case="C2"),
                        data.frame(algo="A2", value=0.7, case="C2"),
                        data.frame(algo="A3", value=0.8, case="C2")
                      ))
 
   data <- rbind(dataTask1, dataTask2, dataTask3)
 
   challenge <- as.challenge(data, by="task", algorithm="algo", case="case", value="value", smallBetter=FALSE)
 
   ranking <- challenge%>%aggregateThenRank(FUN=median, ties.method="min")
 
   meanRanks <- ranking%>%consensus(method = "euclidean")
 
   set.seed(1)
   rankingBootstrapped <- ranking%>%bootstrap(nboot=10)
 
   rankingBootstrapped %>%
     report(consensus=meanRanks,
            title="Test Challenge",
            file="testthat_multi_task_bootstrapping",
            format="PDF",
            clean=TRUE,
            open=FALSE)
 
   expect_true(file.exists("testthat_multi_task_bootstrapping.pdf"))
 
   # Clean up
   if (file.exists("testthat_multi_task_bootstrapping.pdf")) {
     file.remove("testthat_multi_task_bootstrapping.pdf")
   }
 
 })
 
 test_that("HTML report for multi-task data set with bootstrapping is created", {
   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")
                      ))
   dataTask3 <- cbind(task="T3",
                      rbind(
                        data.frame(algo="A1", value=0.1, case="C1"),
                        data.frame(algo="A2", value=0.2, case="C1"),
                        data.frame(algo="A3", value=0.3, case="C1"),
                        data.frame(algo="A1", value=0.6, case="C2"),
                        data.frame(algo="A2", value=0.7, case="C2"),
                        data.frame(algo="A3", value=0.8, case="C2")
                      ))
 
   data <- rbind(dataTask1, dataTask2, dataTask3)
 
   challenge <- as.challenge(data, by="task", algorithm="algo", case="case", value="value", smallBetter=FALSE)
 
   ranking <- challenge%>%aggregateThenRank(FUN=median, ties.method="min")
 
   meanRanks <- ranking%>%consensus(method = "euclidean")
 
   set.seed(1)
   rankingBootstrapped <- ranking%>%bootstrap(nboot=10)
 
   rankingBootstrapped %>%
     report(consensus=meanRanks,
            title="Test Challenge",
            file="testthat_multi_task_bootstrapping",
            format="HTML",
            clean=TRUE,
            open=FALSE)
 
   expect_true(file.exists("testthat_multi_task_bootstrapping.html"))
 
   # Clean up
   if (file.exists("testthat_multi_task_bootstrapping.html")) {
     file.remove("testthat_multi_task_bootstrapping.html")
   }
 
 })
 
 test_that("Word report for multi-task data set with bootstrapping is created", {
   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")
                      ))
   dataTask3 <- cbind(task="T3",
                      rbind(
                        data.frame(algo="A1", value=0.1, case="C1"),
                        data.frame(algo="A2", value=0.2, case="C1"),
                        data.frame(algo="A3", value=0.3, case="C1"),
                        data.frame(algo="A1", value=0.6, case="C2"),
                        data.frame(algo="A2", value=0.7, case="C2"),
                        data.frame(algo="A3", value=0.8, case="C2")
                      ))
 
   data <- rbind(dataTask1, dataTask2, dataTask3)
 
   challenge <- as.challenge(data, by="task", algorithm="algo", case="case", value="value", smallBetter=FALSE)
 
   ranking <- challenge%>%aggregateThenRank(FUN=median, ties.method="min")
 
   meanRanks <- ranking%>%consensus(method = "euclidean")
 
   set.seed(1)
   rankingBootstrapped <- ranking%>%bootstrap(nboot=10)
 
   rankingBootstrapped %>%
     report(consensus=meanRanks,
            title="Test Challenge",
            file="testthat_multi_task_bootstrapping",
            format="Word",
            clean=TRUE,
            open=FALSE)
 
   expect_true(file.exists("testthat_multi_task_bootstrapping.docx"))
 
   # Clean up
   if (file.exists("testthat_multi_task_bootstrapping.docx")) {
     file.remove("testthat_multi_task_bootstrapping.docx")
   }
 
 })
+
+test_that("PDF report for multi-task data set with bootstrapping is created (#algorithms < #tasks)", {
+  dataTask1 <- cbind(task="T1",
+                     rbind(
+                       data.frame(algo="A1", value=0.80, case="C1"),
+                       data.frame(algo="A2", value=0.60, case="C1"),
+                       data.frame(algo="A1", value=0.85, case="C2"),
+                       data.frame(algo="A2", value=0.65, case="C2")
+                     ))
+  dataTask2 <- cbind(task="T2",
+                     rbind(
+                       data.frame(algo="A1", value=0.20, case="C1"),
+                       data.frame(algo="A2", value=0.30, case="C1"),
+                       data.frame(algo="A1", value=0.25, case="C2"),
+                       data.frame(algo="A2", value=0.35, case="C2")
+                     ))
+  dataTask3 <- cbind(task="T3",
+                     rbind(
+                       data.frame(algo="A1", value=0.10, case="C1"),
+                       data.frame(algo="A2", value=0.80, case="C1"),
+                       data.frame(algo="A1", value=0.15, case="C2"),
+                       data.frame(algo="A2", value=0.85, case="C2")
+                     ))
+
+  data <- rbind(dataTask1, dataTask2, dataTask3)
+
+  challenge <- as.challenge(data, by="task", algorithm="algo", case="case", value="value", smallBetter=FALSE)
+
+  ranking <- challenge%>%aggregateThenRank(FUN=median, ties.method="min")
+
+  meanRanks <- ranking%>%consensus(method = "euclidean")
+
+  set.seed(1)
+  rankingBootstrapped <- ranking%>%bootstrap(nboot=10)
+
+  rankingBootstrapped %>%
+    report(consensus=meanRanks,
+           title="Test Challenge",
+           file="testthat_multi_task_bootstrapping_more_tasks_than_algorithms",
+           format="PDF",
+           clean=TRUE,
+           open=FALSE)
+
+  expect_true(file.exists("testthat_multi_task_bootstrapping_more_tasks_than_algorithms.pdf"))
+
+  # Clean up
+  if (file.exists("testthat_multi_task_bootstrapping_more_tasks_than_algorithms.pdf")) {
+    file.remove("testthat_multi_task_bootstrapping_more_tasks_than_algorithms.pdf")
+  }
+
+})
diff --git a/tests/testthat/test-stackedBarPlotStabilityByAlgorithm.R b/tests/testthat/test-stackedBarPlotStabilityByAlgorithm.R
index c07078f..b633905 100644
--- a/tests/testthat/test-stackedBarPlotStabilityByAlgorithm.R
+++ b/tests/testthat/test-stackedBarPlotStabilityByAlgorithm.R
@@ -1,70 +1,139 @@
 # Copyright (c) German Cancer Research Center (DKFZ)
 # All rights reserved.
 #
 # This file is part of challengeR.
 #
 # challengeR is free software: you can redistribute it and/or modify
 # it under the terms of the GNU General Public License as published by
 # the Free Software Foundation, either version 2 of the License, or
 # (at your option) any later version.
 #
 # challengeR is distributed in the hope that it will be useful,
 # but WITHOUT ANY WARRANTY; without even the implied warranty of
 # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
 # GNU General Public License for more details.
 #
 # You should have received a copy of the GNU General Public License
 # along with challengeR. If not, see <https://www.gnu.org/licenses/>.
 
 test_that("stacked bar plot for visualizing ranking stability by algorithm raises error 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)
 
-  expect_error(stabilityByAlgorithm(rankingBootstrapped, stacked =TRUE),
+  expect_error(stabilityByAlgorithm(rankingBootstrapped, stacked = TRUE),
                "The stability of rankings by algorithm cannot be computed for less than two tasks.", fixed=TRUE)
 })
 
 test_that("stacked bar plot for visualizing ranking stability by algorithm 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 <- stabilityByAlgorithm(rankingBootstrapped, stacked =TRUE)
+  actualPlot <- stabilityByAlgorithm(rankingBootstrapped, stacked = TRUE)
+  expect_is(actualPlot, "ggplot")
+})
+
+test_that("stacked bar plot for visualizing ranking stability by algorithm returns one plot if #algorithms equals #tasks", {
+  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="A1", value=0.2, case="C2"),
+                       data.frame(algo="A2", value=0.1, 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="A1", value=0.7, case="C2"),
+                       data.frame(algo="A2", value=0.8, 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)
+
+  meanRanks <- ranking%>%consensus(method = "euclidean")
+
+  actualPlot <- stabilityByAlgorithm(rankingBootstrapped, stacked = TRUE)
+  expect_is(actualPlot, "ggplot")
+})
+
+test_that("stacked bar plot for visualizing ranking stability by algorithm returns one plot if #algorithms < #tasks", {
+  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="A1", value=0.8, case="C2"),
+                       data.frame(algo="A2", value=0.6, 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="A1", value=0.2, case="C2"),
+                       data.frame(algo="A2", value=0.3, case="C2")
+                     ))
+  dataTask3 <- cbind(task="T3",
+                     rbind(
+                       data.frame(algo="A1", value=0.1, case="C1"),
+                       data.frame(algo="A2", value=0.8, case="C1"),
+                       data.frame(algo="A1", value=0.1, case="C2"),
+                       data.frame(algo="A2", value=0.8, case="C2")
+                     ))
+
+  data <- rbind(dataTask1, dataTask2, dataTask3)
+
+  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)
+
+  meanRanks <- ranking%>%consensus(method = "euclidean")
+
+  actualPlot <- stabilityByAlgorithm(rankingBootstrapped, stacked = TRUE)
   expect_is(actualPlot, "ggplot")
 })
diff --git a/tests/testthat/test-stackedFrequencyPlotStabilityByAlgorithm.R b/tests/testthat/test-stackedFrequencyPlotStabilityByAlgorithm.R
index 859cfb4..2c3a9ac 100644
--- a/tests/testthat/test-stackedFrequencyPlotStabilityByAlgorithm.R
+++ b/tests/testthat/test-stackedFrequencyPlotStabilityByAlgorithm.R
@@ -1,108 +1,177 @@
 # Copyright (c) German Cancer Research Center (DKFZ)
 # All rights reserved.
 #
 # This file is part of challengeR.
 #
 # challengeR is free software: you can redistribute it and/or modify
 # it under the terms of the GNU General Public License as published by
 # the Free Software Foundation, either version 2 of the License, or
 # (at your option) any later version.
 #
 # challengeR is distributed in the hope that it will be useful,
 # but WITHOUT ANY WARRANTY; without even the implied warranty of
 # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
 # GNU General Public License for more details.
 #
 # You should have received a copy of the GNU General Public License
 # along with challengeR. If not, see <https://www.gnu.org/licenses/>.
 
 test_that("stacked frequency plot for visualizing ranking stability by algorithm raises error 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)
 
   expect_error(stabilityByAlgorithm(rankingBootstrapped, stacked = TRUE),
                "The stability of rankings by algorithm cannot be computed for less than two tasks.", fixed=TRUE)
 })
 
 test_that("stacked frequency plot for visualizing ranking stability by algorithm 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 <- stabilityByAlgorithm(rankingBootstrapped, stacked = TRUE)
   expect_is(actualPlot, "ggplot")
 })
 
 test_that("stacked frequency plot for visualizing ranking stability by algorithm returns a plot for each algorithm", {
   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)
 
   meanRanks <- ranking%>%consensus(method = "euclidean")
 
   actualPlot <- stabilityByAlgorithm(rankingBootstrapped, ordering = names(meanRanks), stacked = TRUE, single = TRUE)
   expect_equal(length(actualPlot), 3)
   expect_is(actualPlot[[1]], "ggplot")
   expect_is(actualPlot[[2]], "ggplot")
   expect_is(actualPlot[[3]], "ggplot")
 })
+
+test_that("stacked frequency plot for visualizing ranking stability by algorithm returns one plot if #algorithms equals #tasks", {
+  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="A1", value=0.2, case="C2"),
+                       data.frame(algo="A2", value=0.1, 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="A1", value=0.7, case="C2"),
+                       data.frame(algo="A2", value=0.8, 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)
+
+  meanRanks <- ranking%>%consensus(method = "euclidean")
+
+  actualPlot <- stabilityByAlgorithm(rankingBootstrapped, ordering = names(meanRanks), stacked = TRUE, single = FALSE)
+  expect_is(actualPlot, "ggplot")
+})
+
+test_that("stacked frequency plot for visualizing ranking stability by algorithm returns one plot if #algorithms < #tasks", {
+  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="A1", value=0.8, case="C2"),
+                       data.frame(algo="A2", value=0.6, 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="A1", value=0.2, case="C2"),
+                       data.frame(algo="A2", value=0.3, case="C2")
+                     ))
+  dataTask3 <- cbind(task="T3",
+                     rbind(
+                       data.frame(algo="A1", value=0.1, case="C1"),
+                       data.frame(algo="A2", value=0.8, case="C1"),
+                       data.frame(algo="A1", value=0.1, case="C2"),
+                       data.frame(algo="A2", value=0.8, case="C2")
+                     ))
+
+  data <- rbind(dataTask1, dataTask2, dataTask3)
+
+  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)
+
+  meanRanks <- ranking%>%consensus(method = "euclidean")
+
+  actualPlot <- stabilityByAlgorithm(rankingBootstrapped, ordering = names(meanRanks), stacked = TRUE, single = FALSE)
+  expect_is(actualPlot, "ggplot")
+})