diff --git a/tests/testthat/test-bootstrap.R b/tests/testthat/test-bootstrap.R
index e7d6c4e..51b183a 100644
--- a/tests/testthat/test-bootstrap.R
+++ b/tests/testthat/test-bootstrap.R
@@ -1,119 +1,136 @@
-test_that("Single task bootstrapping with 1 test case stopped with message", {
+test_that("single-task bootstrapping with 1 test case stopped with message", {
   dataTask1 <- cbind(task="T1",
                    rbind(
                      data.frame(algo="A1", value=0.8, case="C1"),
                      data.frame(algo="A2", value=0.6, case="C1")
                    ))
 
 
 challenge <- as.challenge(dataTask1,  algorithm="algo", case="case", value="value", smallBetter=FALSE)
 
 ranking <- challenge%>%aggregateThenRank(FUN=median, ties.method="min")
 
 set.seed(1)
-
-
 expect_error(rankingBootstrapped <- ranking%>%bootstrap(nboot=10),
              "Only 1 test case included. Bootstrapping with 1 test case not sensible.", fixed = TRUE)
 })
 
 
-test_that("Multi task bootstrapping, all tasks with 1 test case stopped with message", {
+test_that("multi-task bootstrapping, all tasks with 1 test case stopped with message", {
   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")
   
   set.seed(1)
   expect_error(rankingBootstrapped <- ranking%>%bootstrap(nboot=10),
                "All tasks only contained 1 test case. Bootstrapping with 1 test case not sensible.", fixed = TRUE)
 })
 
 
-test_that("Multi task bootstrapping, only one task with >1 test case continued with message", {
+test_that("multi-task bootstrapping, only one task with >1 test case continued with message", {
   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")
   
   set.seed(1)
   expect_message(rankingBootstrapped <- ranking%>%bootstrap(nboot=3),
                "Task(s) T1, T3 with only 1 test case excluded from bootstrapping.", fixed = TRUE)
 })
 
 
 test_that("two sequential bootstrappings yield same results", {
   data <- read.csv(system.file("extdata", "data_matrix.csv", package="challengeR", mustWork=TRUE))
 
   challenge <- as.challenge(data, by="task", algorithm="alg_name", case="case", value="value", smallBetter=FALSE)
 
   ranking <- challenge%>%rankThenAggregate(FUN=mean, ties.method="min")
 
   set.seed(1)
   rankingBootstrapped1 <- ranking%>%bootstrap(nboot=10)
 
   set.seed(1)
   rankingBootstrapped2 <- ranking%>%bootstrap(nboot=10)
 
   expect_equal(rankingBootstrapped1, rankingBootstrapped2)
 })
 
 
 test_that("two parallel bootstrappings yield same results", {
   data <- read.csv(system.file("extdata", "data_matrix.csv", package="challengeR", mustWork=TRUE))
 
   challenge <- as.challenge(data, by="task", algorithm="alg_name", case="case", value="value", smallBetter=FALSE)
 
   ranking <- challenge%>%rankThenAggregate(FUN=mean, ties.method="min")
 
   library(doParallel)
   numCores <- detectCores(logical=FALSE)
   registerDoParallel(cores=numCores)
 
   set.seed(1, kind="L'Ecuyer-CMRG")
   rankingBootstrapped1 <- ranking%>%bootstrap(nboot=10, parallel=TRUE, progress="none")
 
   set.seed(1, kind="L'Ecuyer-CMRG")
   rankingBootstrapped2 <- ranking%>%bootstrap(nboot=10, parallel=TRUE, progress="none")
 
   stopImplicitCluster()
 
   expect_equal(rankingBootstrapped1, rankingBootstrapped2)
 })
 
+
+test_that("parallel bootstrapping raises warning if RNG \"L'Ecuyer-CMRG\" is not used", {
+  data <- read.csv(system.file("extdata", "data_matrix.csv", package="challengeR", mustWork=TRUE))
+
+  challenge <- as.challenge(data, by="task", algorithm="alg_name", case="case", value="value", smallBetter=FALSE)
+
+  ranking <- challenge%>%rankThenAggregate(FUN=mean, ties.method="min")
+
+  library(doParallel)
+  numCores <- detectCores(logical=FALSE)
+  registerDoParallel(cores=numCores)
+
+  set.seed(1, kind="Super-Duper")
+
+  expect_warning(rankingBootstrapped <- ranking%>%bootstrap(nboot=10, parallel=TRUE, progress="none"),
+                 "To ensure reproducibility please use kind = \"L'Ecuyer-CMRG\" in set.seed(), e.g. set.seed(1, kind = \"L'Ecuyer-CMRG\").", fixed = TRUE)
+
+  stopImplicitCluster()
+})