
library(testthat)

source("user_code.R")
test_that("returns a list with indices and values elements", {
  result <- find_sales_outliers(c(1,2,3,100))
  expect_true(is.list(result), info = "Result should be a list.")
  expect_true("indices" %in% names(result), info = "List should contain 'indices' element.")
  expect_true("values" %in% names(result), info = "List should contain 'values' element.")
})

test_that("correctly identifies outliers above and below bounds", {
  sales <- c(10, 12, 13, 14, 15, 16, 17, 18, 100, 2)
  result <- find_sales_outliers(sales)
  expect_equal(sort(result$indices), sort(c(9,10)), info = "Indices of outliers should be 9 and 10.")
  expect_equal(sort(result$values), sort(c(100, 2)), info = "Values of outliers should be 100 and 2.")
})

test_that("handles vectors with no outliers", {
  sales <- c(10, 12, 14, 16, 18)
  result <- find_sales_outliers(sales)
  expect_equal(length(result$indices), 0, info = "Should return empty indices when no outliers.")
  expect_equal(length(result$values), 0, info = "Should return empty values when no outliers.")
})

test_that("works with outliers at the beginning and end of the vector", {
  sales <- c(100, 11, 12, 13, 14, 15, 16, 17, 18, 200)
  result <- find_sales_outliers(sales)
  expect_true(1 %in% result$indices && 10 %in% result$indices, info = "Should detect outliers at position 1 and 10.")
  expect_true(100 %in% result$values && 200 %in% result$values, info = "Should detect outlier values 100 and 200.")
})

# test_that("accurately detects multiple outliers in the same vector", {
#   sales <- c(5, 7, 8, 9, 10, 100, 101, 102)
#   result <- find_sales_outliers(sales)
#   expect_true(all(c(6,7,8) %in% result$indices), info = "Should detect all upper outliers.")
#   expect_true(100 %in% result$values && 101 %in% result$values && 102 %in% result$values, info = "Should detect all upper outlier values.")
# })

test_main.R

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Challenge: Find Outliers in Sales Data

Ratkaisu

Challenge: Find Outliers in Sales Data

Ratkaisu