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Full Solutions Released for 2022 Kakao New Graduate Recruitment First Coding Test

·2022.01.14 00:00

Key point

Solutions and accuracy rate data for all 7 problems from the 2022 Kakao new graduate recruitment first coding test have been released.

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Details

Solutions for the 2022 Kakao new graduate recruitment first online coding test (5 hours, 7 problems) have been released. This release includes solutions for all 7 problems and the accuracy rate for each problem.

Key Problem Solutions

  • Problem 1 (Report Result): Accuracy rate 80.13%. Uses a hash data structure to handle duplicate reports and implements logic to send mail to users who meet the suspension criteria.
  • Problem 2 (Counting Primes in Base k): Accuracy rate 55.82%. Converts the number base, parses by 0, and identifies primes. Primes can be identified using the Sieve of Eratosthenes or by dividing up to the square root.
  • Problem 3 (Parking Fee Calculation): Accuracy rate 73.10%. Converts entry/exit times to minutes to calculate cumulative parking time and determines the billed fee according to the fee schedule.
  • Problem 4 (Archery Competition): Accuracy rate 21.16%. A problem requiring the calculation of arrow placement for Ryan to defeat Apeach by the largest score difference, solved using exhaustive search with DFS or bit masking.
  • Problem 5 (Sheep and Wolves): Accuracy rate 7.76%. A problem requiring the maximum number of sheep that can be collected in a binary tree structure without being eaten by wolves, solved using exhaustive search with DFS.
  • Problem 6 (Undestroyed Buildings): Accuracy rate 51.11%, efficiency 1.86%. Calculates the number of undestroyed buildings after applying attack/recovery skills to rectangular ranges on an N x M map. Since brute force causes time limit exceeded, it is solved with O(K + N*M) time complexity using 2D cumulative sum (difference array).
  • Problem 7 (Disappearing Platforms): Accuracy rate 0.78%. Determines whether player A wins on a board with disappearing platforms and the minimum number of moves. Since the board size is small and the search space is limited by platform disappearance, exhaustive search (recursion) is used, implementing so that the winner minimizes moves and the loser maximizes moves.

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