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katrinleinweber's solution

to Rotational Cipher in the R Track

Published at Jul 13 2018 · 1 comment
Test suite

Create an implementation of the rotational cipher, also sometimes called the Caesar cipher.

The Caesar cipher is a simple shift cipher that relies on transposing all the letters in the alphabet using an integer key between 0 and 26. Using a key of 0 or 26 will always yield the same output due to modular arithmetic. The letter is shifted for as many values as the value of the key.

The general notation for rotational ciphers is ROT + <key>. The most commonly used rotational cipher is ROT13.

A ROT13 on the Latin alphabet would be as follows:

Plain:  abcdefghijklmnopqrstuvwxyz
Cipher: nopqrstuvwxyzabcdefghijklm

It is stronger than the Atbash cipher because it has 27 possible keys, and 25 usable keys.

Ciphertext is written out in the same formatting as the input including spaces and punctuation.


  • ROT5 omg gives trl
  • ROT0 c gives c
  • ROT26 Cool gives Cool
  • ROT13 The quick brown fox jumps over the lazy dog. gives Gur dhvpx oebja sbk whzcf bire gur ynml qbt.
  • ROT13 Gur dhvpx oebja sbk whzcf bire gur ynml qbt. gives The quick brown fox jumps over the lazy dog.


See this guide for instructions on how to setup your local R environment.

How to implement your solution

In each problem folder, there is a file named <exercise_name>.R containing a function that returns a NULL value. Place your implementation inside the body of the function.

How to run tests

Inside of RStudio, simply execute the test_<exercise_name>.R script. This can be conveniently done with testthat's auto_test function. Because exercism code and tests are in the same folder, use this same path for both code_path and test_path parameters. On the command-line, you can also run Rscript test_<exercise_name>.R.


Wikipedia https://en.wikipedia.org/wiki/Caesar_cipher

Submitting Incomplete Solutions

It's possible to submit an incomplete solution so you can see how others have completed the exercise.



context("rotational cipher")

test_that("rotate a by 1", {
  text <- "a"
  key <- 1
  expect_equal(rotate(text, key), "b")

test_that("rotate a by 26, same output as input", {
  text <- "a"
  key <- 26
  expect_equal(rotate(text, key), "a")

test_that("rotate a by 0, same output as input", {
  text <- "a"
  key <- 0
  expect_equal(rotate(text, key), "a")

test_that("rotate m by 13", {
  text <- "m"
  key <- 13
  expect_equal(rotate(text, key), "z")

test_that("rotate n by 13 with wrap around alphabet", {
  text <- "n"
  key <- 13
  expect_equal(rotate(text, key), "a")

test_that("rotate capital letters", {
  text <- "OMG"
  key <- 5
  expect_equal(rotate(text, key), "TRL")

test_that("rotate spaces", {
  text <- "O M G"
  key <- 5
  expect_equal(rotate(text, key), "T R L")

test_that("rotate numbers", {
  text <- "Testing 1 2 3 testing"
  key <- 4
  expect_equal(rotate(text, key), "Xiwxmrk 1 2 3 xiwxmrk")

test_that("rotate punctuation", {
  text <- "Let's eat, Grandma!"
  key <- 21
  expect_equal(rotate(text, key), "Gzo'n zvo, Bmviyhv!")

test_that("rotate all letters", {
  text <- "The quick brown fox jumps over the lazy dog."
  key <- 13
  expect_equal(rotate(text, key), 
               "Gur dhvpx oebja sbk whzcf bire gur ynml qbt.")

message("All tests passed for exercise: rotational-cipher")

rotate <- function(text, key) {
  shift <- function(byte) {
    # define alphabet boundaries for ASCII decimals, to enable shifting
    wrap <- 26
    A <- 65
    Z <- 90
    a <- 97
    z <- 122
    if      (between(byte, A, Z)) return((byte - A + key) %% wrap + A)
    else-if (between(byte, a, z)) return((byte - a + key) %% wrap + a)
    else    return(byte)   #   set decimal to 1 ^      reset range ^
  # convert text to ASCII decimals
  # convert back to (cipher)text
  text %>% 
    utf8ToInt() %>% 
    purrr::map(shift) %>% 
    intToUtf8  # %>% return()

Community comments

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Avatar of katrinleinweber

Comparing this with a solution that doesn't use the magrittr pipe in microbenchmark shows how large the %>%'s performance hit is.

It looks so clean, but I guess as soon as your pipeline runs for longer than a few minutes repeatedly, investing those few minutes to refactor your code into a series of intermediately <--assigned variables pays off in the long run.

What can you learn from this solution?

A huge amount can be learned from reading other people’s code. This is why we wanted to give exercism users the option of making their solutions public.

Here are some questions to help you reflect on this solution and learn the most from it.

  • What compromises have been made?
  • Are there new concepts here that you could read more about to improve your understanding?