2021 Day 10

— Day 10: Syntax Scoring —

The navigation subsystem is corrupted! There are so many brackets.

Find the first illegal character in each corrupted line of the navigation subsystem. What is the total syntax error score for those errors?

library(tidyverse)

my_file <- here::here("2021", "data-2021-10.txt")
x <- readLines(my_file)

Write a function to get the error bracket

return_error <- function(x) {
  new = x
  pairs = c("\\[\\]", "\\(\\)", "\\{\\}", "\\<\\>")
  backs = "[\\)\\}\\]\\>]"

  repeat {
    old = new
    for (j in seq_along(pairs)) {
      new = str_replace_all(new, pairs[j], "")
    }
    if (old == new) break
  }

  str_match(new, backs)[[1]]
}

Simple script to loop through the inputs and assign scores

# replace the inner matches until we can replace no more
pieces = tibble(parts = x) %>%
    rowwise() %>%
    mutate(closer = return_error(parts))

points = tribble(
    ~closer, ~points,
    ")", 3,
    "]", 57,
    "}", 1197,
    ">", 25137,
  )

part_one = inner_join(pieces, points, by='closer')
sum(part_one$points)

[1] 318099

— Part Two —

Find the completion string for each incomplete line, score the completion strings, and sort the scores. What is the middle score?

return_closers <- function(x) {
  new = x
  pairs = c("\\[\\]", "\\(\\)", "\\{\\}", "\\<\\>")
  openers = c("\\[", "\\(", "\\{", "\\<")
  closers = c("\\]", "\\)", "\\}", "\\>")
  backs = "[\\)\\}\\]\\>]"

  repeat {
    old = new
    for (j in seq_along(pairs)) {
      new = str_replace_all(new, pairs[j], "")
    }
    if (old == new) break
  }

  if (!is.na(str_match(new, backs)[[1]])) return("")

  forward = stringi::stri_reverse(new)

  backward = forward
  for (k in seq_along(openers)) {
    backward = str_replace_all(backward, openers[k], closers[k])
  }
  return(backward)
}

score_seq <- function(z) {
  pp = unlist(strsplit(z, ""))

  cc = ")]}>"

  ss = 0
  for (j in seq_along(pp)) {
    ss = ss * 5
    ss = ss + str_locate(cc, paste0("\\", pp[[j]]))[[1]]
  }
  return(ss)
}

Again, create functions and then use those for a nice tibble

pieces = tibble(parts = x) %>%
    rowwise() %>%
    mutate(closer = return_closers(parts),
           scores = score_seq(closer)) %>%
    filter(scores != 0)

scores = sort(pieces$scores)
scores[ceiling(length(scores) / 2)]

[1] 2389738699