diff --git a/tests/testthat/test-taskSubset.R b/tests/testthat/test-taskSubset.R
index 2efd8ab..aa54558 100644
--- a/tests/testthat/test-taskSubset.R
+++ b/tests/testthat/test-taskSubset.R
@@ -1,185 +1,180 @@
 test_that("extraction of task subset works 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=mean, ties.method="min")
 
   rankingSubset <- subset(ranking, tasks=c("T2"))
 
   expect_equal(length(rankingSubset$matlist), 1)
   expect_is(rankingSubset$matlist$T2, "data.frame")
 
   expect_equal(length(rankingSubset$data), 1)
   expect_is(rankingSubset$data$T2, "data.frame")
 })
 
 test_that("extraction of task subset works 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=mean, ties.method="min")
 
   rankingSubset <- subset(ranking, tasks=c("T1"))
 
   expect_equal(length(rankingSubset$matlist), 1)
   expect_is(rankingSubset$matlist$T1, "data.frame")
 
   expect_equal(length(rankingSubset$data), 1)
   expect_is(rankingSubset$data$T1, "data.frame")
 })
 
-test_that("extraction of task subset does not raise an error for invalid task name", {
+test_that("extraction of task subset raises an error for invalid task name", {
   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=mean, ties.method="min")
 
-  rankingSubset <- subset(ranking, tasks=c("T1x"))
-
-  expect_equal(length(rankingSubset$matlist), 1)
-  expect_equal(rankingSubset$matlist$T1, NULL)
-
-  expect_equal(length(rankingSubset$data), 1)
-  expect_equal(rankingSubset$data$T1, NULL)
+  expect_error(subset(ranking, tasks=c("T1x")),
+               "There is/are no task(s) called T1x.", fixed=TRUE)
 })
 
 test_that("extraction of task subset from bootstrap ranking works 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=mean, ties.method="min")
 
   set.seed(1)
   rankingBootstrapped <- ranking%>%bootstrap(nboot=10)
 
   rankingBootstrappedSubset <- subset(rankingBootstrapped, tasks=c("T2"))
 
   expect_equal(length(rankingBootstrappedSubset$matlist), 1)
   expect_is(rankingBootstrappedSubset$matlist$T2, "data.frame")
 
   expect_equal(length(rankingBootstrappedSubset$data), 1)
   expect_is(rankingBootstrappedSubset$data$T2, "data.frame")
 
   expect_equal(length(rankingBootstrappedSubset$bootsrappedRanks), 1)
   expect_is(rankingBootstrappedSubset$bootsrappedRanks$T2, "data.frame")
 
   expect_equal(length(rankingBootstrappedSubset$bootsrappedAggregate), 1)
   expect_is(rankingBootstrappedSubset$bootsrappedAggregate$T2, "data.frame")
 })
 
 test_that("extraction of task subset from bootstrap ranking works 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=mean, ties.method="min")
 
   set.seed(1)
   rankingBootstrapped <- ranking%>%bootstrap(nboot=10)
 
   rankingBootstrappedSubset <- subset(rankingBootstrapped, tasks=c("T1"))
 
   expect_equal(length(rankingBootstrappedSubset$matlist), 1)
   expect_is(rankingBootstrappedSubset$matlist$T1, "data.frame")
 
   expect_equal(length(rankingBootstrappedSubset$data), 1)
   expect_is(rankingBootstrappedSubset$data$T1, "data.frame")
 
   expect_equal(length(rankingBootstrappedSubset$bootsrappedRanks), 1)
   expect_is(rankingBootstrappedSubset$bootsrappedRanks$T1, "data.frame")
 
   expect_equal(length(rankingBootstrappedSubset$bootsrappedAggregate), 1)
   expect_is(rankingBootstrappedSubset$bootsrappedAggregate$T1, "data.frame")
 })
 
 test_that("extraction of task subset from bootstrap ranking does not raise an error for invalid task name", {
   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=mean, ties.method="min")
 
   set.seed(1)
   rankingBootstrapped <- ranking%>%bootstrap(nboot=10)
 
   rankingBootstrappedSubset <- subset(rankingBootstrapped, tasks=c("T1x"))
 
   expect_equal(length(rankingBootstrappedSubset$matlist), 1)
   expect_equal(rankingBootstrappedSubset$matlist$T1, NULL)
 
   expect_equal(length(rankingBootstrappedSubset$data), 1)
   expect_equal(rankingBootstrappedSubset$data$T1, NULL)
 
   expect_equal(length(rankingBootstrappedSubset$bootsrappedRanks), 1)
   expect_equal(rankingBootstrappedSubset$bootsrappedRanks$T1, NULL)
 
   expect_equal(length(rankingBootstrappedSubset$bootsrappedAggregate), 1)
   expect_equal(rankingBootstrappedSubset$bootsrappedAggregate$T1, NULL)
 })