diff --git a/DESCRIPTION b/DESCRIPTION
index 484ed9819..d8e0d4125 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,8 +1,8 @@
 Type: Package
 Package: teal.modules.general
 Title: General Modules for 'teal' Applications
-Version: 0.3.0.9010
-Date: 2024-04-18
+Version: 0.3.0.9012
+Date: 2024-04-19
 Authors@R: c(
     person("Dawid", "Kaledkowski", , "dawid.kaledkowski@roche.com", role = c("aut", "cre")),
     person("Pawel", "Rucki", , "pawel.rucki@roche.com", role = "aut"),
diff --git a/NEWS.md b/NEWS.md
index 5e074467f..220427adc 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -1,4 +1,4 @@
-# teal.modules.general 0.3.0.9010
+# teal.modules.general 0.3.0.9012
 
 # teal.modules.general 0.3.0
 
diff --git a/tests/testthat/test-shinytest2-tm_g_scatterplotmatrix.R b/tests/testthat/test-shinytest2-tm_g_scatterplotmatrix.R
new file mode 100644
index 000000000..1f1b6e7e9
--- /dev/null
+++ b/tests/testthat/test-shinytest2-tm_g_scatterplotmatrix.R
@@ -0,0 +1,113 @@
+app_driver_tm_g_scatterplotmatrix <- function() { # nolint: object_length_linter.
+  data <- simple_cdisc_data()
+  init_teal_app_driver(
+    data = data,
+    modules = tm_g_scatterplotmatrix(
+      label = "Scatterplot matrix",
+      variables = list(
+        teal.transform::data_extract_spec(
+          dataname = "ADSL",
+          select = teal.transform::select_spec(
+            label = "Select variables:",
+            choices = teal.transform::variable_choices(data[["ADSL"]]),
+            selected = c("AGE", "RACE", "SEX"),
+            multiple = TRUE,
+            ordered = TRUE,
+            fixed = FALSE
+          )
+        ),
+        teal.transform::data_extract_spec(
+          dataname = "ADRS",
+          filter = teal.transform::filter_spec(
+            label = "Select endpoints:",
+            vars = c("PARAMCD", "AVISIT"),
+            choices = teal.transform::value_choices(data[["ADRS"]], c("PARAMCD", "AVISIT"), c("PARAM", "AVISIT")),
+            selected = "INVET - END OF INDUCTION",
+            multiple = TRUE
+          ),
+          select = teal.transform::select_spec(
+            label = "Select variables:",
+            choices = teal.transform::variable_choices(data[["ADRS"]]),
+            selected = c("AGE", "AVAL", "ADY"),
+            multiple = TRUE,
+            ordered = TRUE,
+            fixed = FALSE
+          )
+        )
+      ),
+      plot_height = c(600, 200, 2000),
+      plot_width = NULL,
+      pre_output = NULL,
+      post_output = NULL
+    ),
+    timeout = 3000
+  )
+}
+
+test_that("e2e - tm_g_scatterplotmatrix: Initializes without errors", {
+  skip_if_too_deep(5)
+  app_driver <- app_driver_tm_g_scatterplotmatrix()
+
+  app_driver$expect_no_shiny_error()
+
+  testthat::expect_equal(
+    app_driver$get_text("#teal-main_ui-root-active_tab > li.active > a"),
+    "Scatterplot matrix"
+  )
+
+  encoding_dataset <- app_driver$get_text("#teal-main_ui-root-scatterplot_matrix .help-block")
+  testthat::expect_match(encoding_dataset, "Datasets.*ADSL.*ADRS", all = FALSE)
+
+  app_driver$stop()
+})
+
+test_that("e2e - tm_g_scatterplotmatrix: Verify module displays data table", {
+  skip_if_too_deep(5)
+  app_driver <- app_driver_tm_g_scatterplotmatrix()
+
+  # table
+  testthat::expect_true(app_driver$is_visible(selector = app_driver$active_module_element("myplot-plot_out_main")))
+
+  app_driver$stop()
+})
+
+test_that("e2e - tm_g_scatterplotmatrix: Verify default values and settings (data_extracts) for data selection", {
+  skip_if_too_deep(5)
+  app_driver <- app_driver_tm_g_scatterplotmatrix()
+
+  # default variable selection
+  dataset <- app_driver$get_active_module_input("variables-dataset")
+  variables <- app_driver$get_active_module_input(sprintf(
+    "variables-dataset_%s_singleextract-select",
+    dataset
+  ))
+  testthat::expect_equal(
+    dataset,
+    "ADSL"
+  )
+  testthat::expect_equal(
+    variables,
+    c("AGE", "SEX", "RACE")
+  )
+
+  # new variable selection
+  app_driver$set_active_module_input("variables-dataset", "ADRS")
+  app_driver$set_active_module_input("dataset_ADRS_singleextract-select", c("SEX", "RACE", "ETHNIC"))
+  app_driver$expect_no_validation_error()
+
+  app_driver$stop()
+})
+
+test_that("e2e - tm_g_scatterplotmatrix: Change plot settings", {
+  skip_if_too_deep(5)
+  app_driver <- app_driver_tm_g_scatterplotmatrix()
+
+  app_driver$set_active_module_input("alpha", 0.7)
+  app_driver$set_active_module_input("cex", 2)
+
+  app_driver$expect_no_validation_error()
+
+  app_driver$click(selector = app_driver$active_module_element("cor"))
+  app_driver$expect_no_validation_error()
+  app_driver$stop()
+})
diff --git a/tests/testthat/test-shinytest2-tm_outliers.R b/tests/testthat/test-shinytest2-tm_outliers.R
new file mode 100644
index 000000000..49065a963
--- /dev/null
+++ b/tests/testthat/test-shinytest2-tm_outliers.R
@@ -0,0 +1,313 @@
+app_driver_tm_outlier <- function() {
+  data <- teal.data::teal_data()
+  data <- within(data, {
+    CO2 <- CO2 # nolint: object_name
+    CO2[["primary_key"]] <- seq_len(nrow(CO2)) # nolint: object_name
+  })
+  teal.data::datanames(data) <- "CO2"
+  teal.data::join_keys(data) <- teal.data::join_keys(join_key("CO2", "CO2", "primary_key"))
+
+  vars <- teal.transform::choices_selected(
+    teal.transform::variable_choices(
+      data[["CO2"]],
+      c("Plant", "Type", "Treatment")
+    )
+  )
+
+  init_teal_app_driver(
+    data = data,
+    modules = tm_outliers(
+      outlier_var = list(
+        teal.transform::data_extract_spec(
+          dataname = "CO2",
+          select = teal.transform::select_spec(
+            label = "Select variable:",
+            choices = teal.transform::variable_choices(data[["CO2"]], c("conc", "uptake")),
+            selected = "uptake",
+            multiple = FALSE,
+            fixed = FALSE
+          )
+        )
+      ),
+      categorical_var = list(
+        teal.transform::data_extract_spec(
+          dataname = "CO2",
+          filter = teal.transform::filter_spec(
+            vars = vars,
+            choices = teal.transform::value_choices(data[["CO2"]], vars$selected),
+            selected = teal.transform::value_choices(data[["CO2"]], vars$selected),
+            multiple = TRUE
+          )
+        )
+      ),
+      ggplot2_args = list(
+        teal.widgets::ggplot2_args(
+          labs = list(subtitle = "Plot generated by Outliers Module")
+        )
+      )
+    )
+  )
+}
+
+testthat::test_that("e2e - tm_outliers: data parameter and module label is passed properly", {
+  skip_if_too_deep(5)
+
+  app_driver <- app_driver_tm_outlier()
+  app_driver$expect_no_shiny_error()
+
+  testthat::expect_equal(
+    app_driver$get_text("#teal-main_ui-root-active_tab > li.active > a"),
+    "Outliers Module"
+  )
+
+  encoding_dataset <- app_driver$get_text("#teal-main_ui-root-outliers_module .help-block")
+  testthat::expect_match(encoding_dataset, "Dataset:[\n ]*CO2", all = FALSE)
+  testthat::expect_match(encoding_dataset, "Outlier data points", all = FALSE)
+
+  app_driver$stop()
+})
+
+testthat::test_that("e2e - tm_outliers:
+  data extract spec elements are initialized with the default values
+  specified by outlier_var and categorical_var argument", {
+  skip_if_too_deep(5)
+
+  app_driver <- app_driver_tm_outlier()
+  app_driver$expect_no_shiny_error()
+
+  testthat::expect_identical(
+    app_driver$get_active_module_input("outlier_var-dataset_CO2_singleextract-select"),
+    "uptake"
+  )
+  app_driver$set_active_module_input("outlier_var-dataset_CO2_singleextract-select", "conc")
+  app_driver$expect_no_validation_error()
+
+  testthat::expect_identical(
+    app_driver$get_active_module_input("categorical_var-dataset_CO2_singleextract-filter1-col"),
+    "Plant"
+  )
+
+  testthat::expect_identical(
+    app_driver$get_active_module_input("categorical_var-dataset_CO2_singleextract-filter1-vals"),
+    c(
+      "Qn1", "Qn2", "Qn3", "Qc1", "Qc2", "Qc3", "Mn1", "Mn2", "Mn3",
+      "Mc1", "Mc2", "Mc3"
+    )
+    # THIS WILL HAVE DIFFERENT ORDER ONCE THIS IS FIXED
+    # https://github.com/insightsengineering/teal.modules.general/issues/735
+  )
+  app_driver$set_active_module_input("categorical_var-dataset_CO2_singleextract-filter1-col", c("Qn1", "Qn2", "Qn3"))
+  app_driver$expect_no_shiny_error()
+
+  app_driver$set_active_module_input("categorical_var-dataset_CO2_singleextract-filter1-col", "Type")
+  app_driver$expect_no_shiny_error()
+
+  app_driver$stop()
+})
+
+testthat::test_that("e2e - tm_outliers: default plot_type is set properly and has proper possible choices", {
+  skip_if_too_deep(5)
+
+  app_driver <- app_driver_tm_outlier()
+  app_driver$expect_no_shiny_error()
+
+  testthat::expect_identical(app_driver$get_active_module_input("boxplot_alts"), "Box plot")
+
+  plot_choices <- app_driver$active_module_element_text("boxplot_alts")
+  testthat::expect_match(plot_choices, "Violin plot", fixed = TRUE)
+
+  app_driver$set_active_module_input("boxplot_alts", "Violin plot")
+  app_driver$expect_no_shiny_error()
+
+  app_driver$stop()
+})
+
+testthat::test_that("e2e - tm_outliers: module is divided into 3 tabs", {
+  skip_if_too_deep(5)
+
+  app_driver <- app_driver_tm_outlier()
+  app_driver$expect_no_shiny_error()
+
+  testthat::expect_identical(app_driver$get_active_module_input("tabs"), "Boxplot")
+  testthat::expect_match(
+    app_driver$active_module_element_text("tabs"),
+    "Boxplot.*Density Plot.*Cumulative Distribution Plot",
+    fixed = FALSE
+  )
+  app_driver$stop()
+})
+
+testthat::test_that("e2e - tm_outliers: plot_type is hidden when Boxplot tab is not selected", {
+  skip_if_too_deep(5)
+
+  app_driver <- app_driver_tm_outlier()
+  app_driver$expect_no_shiny_error()
+
+  testthat::expect_true(app_driver$is_visible(app_driver$active_module_element("boxplot_alts")))
+
+  app_driver$set_active_module_input("tabs", "Density Plot")
+  testthat::expect_false(app_driver$is_visible(app_driver$active_module_element("boxplot_alts")))
+
+  app_driver$set_active_module_input("tabs", "Cumulative Distribution Plot")
+  testthat::expect_false(app_driver$is_visible(app_driver$active_module_element("boxplot_alts")))
+
+  app_driver$stop()
+})
+
+testthat::test_that("e2e - tm_outliers: default radio buttons are set properly", {
+  skip_if_too_deep(5)
+
+  app_driver <- app_driver_tm_outlier()
+  app_driver$expect_no_shiny_error()
+
+  testthat::expect_false(app_driver$get_active_module_input("split_outliers"))
+  testthat::expect_false(app_driver$get_active_module_input("order_by_outlier"))
+
+  app_driver$set_active_module_input("split_outliers", TRUE)
+  app_driver$set_active_module_input("order_by_outlier", TRUE)
+  app_driver$expect_no_shiny_error()
+
+  app_driver$stop()
+})
+
+testthat::test_that("e2e - tm_outliers: method parameters are set properly", {
+  skip_if_too_deep(5)
+
+  app_driver <- app_driver_tm_outlier()
+  app_driver$expect_no_shiny_error()
+
+  testthat::expect_identical(app_driver$get_active_module_input("method"), "IQR")
+  method_choices <- app_driver$active_module_element_text("method")
+  testthat::expect_match(method_choices, "Z-score", fixed = TRUE)
+  testthat::expect_match(method_choices, "Percentile", fixed = TRUE)
+
+  app_driver$stop()
+})
+
+
+testthat::test_that("e2e - tm_outliers: outlier definition text and range are displayed properly depending on method", {
+  skip_if_too_deep(5)
+
+  app_driver <- app_driver_tm_outlier()
+  app_driver$expect_no_shiny_error()
+
+  # Initially only the first slider should be visible.
+  testthat::expect_true(app_driver$is_visible(app_driver$active_module_element("iqr_slider")))
+  testthat::expect_false(app_driver$is_visible(app_driver$active_module_element("zscore_slider")))
+  testthat::expect_false(app_driver$is_visible(app_driver$active_module_element("percentile_slider")))
+
+  # IQR METHOD
+  testthat::expect_identical(app_driver$get_active_module_input("method"), "IQR")
+  testthat::expect_match(
+    app_driver$active_module_element_text("ui_outlier_help"),
+    "x<Q1−3×IQRx<Q1−3×IQRx",
+    fixed = TRUE
+  )
+  testthat::expect_identical(app_driver$get_active_module_input("iqr_slider"), 3L)
+  app_driver$set_active_module_input("iqr_slider", 8L)
+  app_driver$expect_no_shiny_error()
+
+  # Z-score METHOD
+  app_driver$set_active_module_input("method", "Z-score")
+  app_driver$expect_no_shiny_error()
+  testthat::expect_true(app_driver$is_visible(app_driver$active_module_element("zscore_slider")))
+  testthat::expect_match(
+    app_driver$active_module_element_text("ui_outlier_help"),
+    "Zscore(x)<−3Zscore(x)<−3Zscore(x)",
+    fixed = TRUE
+  )
+  testthat::expect_identical(app_driver$get_active_module_input("zscore_slider"), 3L)
+  app_driver$set_active_module_input("zscore_slider", 5L)
+  app_driver$expect_no_shiny_error()
+
+  # Percentile METHOD
+  app_driver$set_active_module_input("method", "Percentile")
+  app_driver$expect_no_shiny_error()
+  testthat::expect_true(app_driver$is_visible(app_driver$active_module_element("percentile_slider")))
+  testthat::expect_match(
+    app_driver$active_module_element_text("ui_outlier_help"),
+    "Percentile(x)<0.01Percentile(x)<0.01 Percentile(x)",
+    fixed = TRUE
+  )
+  testthat::expect_identical(app_driver$get_active_module_input("percentile_slider"), 0.01)
+  app_driver$set_active_module_input("percentile_slider", 0.05)
+  app_driver$expect_no_shiny_error()
+
+  app_driver$stop()
+})
+
+testthat::test_that("e2e - tm_outliers: outliers summary table is displayed with proper content", {
+  skip_if_too_deep(5)
+
+  app_driver <- app_driver_tm_outlier()
+  app_driver$expect_no_shiny_error()
+
+  # Initial state.
+  testthat::expect_identical(
+    app_driver$active_module_element_text("total_outliers"),
+    "Total number of outlier(s): 0 / 84 [0.00%]"
+  )
+
+  table_text <- app_driver$active_module_element_text("summary_table")
+  testthat::expect_match(table_text, "Outliers.*Missing.*Total")
+  statistics <- app_driver$get_active_module_input("categorical_var-dataset_CO2_singleextract-filter1-vals")
+  testthat::expect_match(table_text, paste(statistics, collapse = "|"), fixed = FALSE)
+
+  # Change method to Z-score and adjust slider.
+  app_driver$set_active_module_input("method", "Z-score")
+  app_driver$set_active_module_input("zscore_slider", 1.5)
+  testthat::expect_identical(
+    app_driver$active_module_element_text("total_outliers"),
+    "Total number of outlier(s): 8 / 84 [9.52%]"
+  )
+  table_text <- app_driver$active_module_element_text("summary_table")
+  testthat::expect_match(
+    table_text,
+    "01 [14.29%]2 [28.57%]001 [14.29%]001 [14.29%]1 [14.29%]1 [14.29%]1 [14.29%]",
+    fixed = TRUE
+  )
+
+  # Select split outliers.
+  app_driver$set_active_module_input("split_outliers", TRUE)
+  testthat::expect_identical(
+    app_driver$active_module_element_text("total_outliers"),
+    "Total number of outlier(s): 12 / 84 [14.29%]"
+  )
+  table_text <- app_driver$active_module_element_text("summary_table")
+  testthat::expect_match(
+    table_text,
+    "1 [14.29%]1 [14.29%]1 [14.29%]1 [14.29%]1 [14.29%]1 [14.29%]1 [14.29%]1",
+    fixed = TRUE
+  )
+
+
+  app_driver$stop()
+})
+
+
+testthat::test_that("e2e - tm_outliers: outlier table is displayed with proper content", {
+  skip_if_too_deep(5)
+
+  app_driver <- app_driver_tm_outlier()
+  app_driver$expect_no_shiny_error()
+
+  app_driver$set_active_module_input("method", "Z-score")
+  app_driver$set_active_module_input("zscore_slider", 1.5)
+
+  table_content <- app_driver$active_module_element_text("table_ui")
+
+  test_match <- function(x) {
+    testthat::expect_match(
+      table_content,
+      paste(x, collapse = ""),
+      fixed = TRUE
+    )
+  }
+
+  test_match(c("primary_key", "uptake", "Plant"))
+  test_match(c("1", "14", "44.3", "Qn2"))
+  test_match(c("4", "29", "9.3", "Qc2"))
+  test_match(c("8", "78", "10.6", "Mc3"))
+
+  app_driver$stop()
+})