LeetCode: Maximum Length of Repeated Subarray Solution

Memoized recursion, somewhat similar to "Longest common subsequence"

Approach

recursion(i, j)
returns longest common post-fix of
nums1.slice(0, i)
and
nums2.slice(0, j)

Result will be

max(recursion(i, j))
all over
i, j
pairs

Implementation

1/**
2 * @param {number[]} nums1
3 * @param {number[]} nums2
4 * @return {number}
5 */
6var findLength = function (nums1, nums2) {
7 const [m, n] = [nums1.length, nums2.length]
8 const memo = Array.from({ length: m }, _ => Array(n).fill(null))
9
10 const recursion = (i, j) => {
11 if (i < 0 || j < 0) return 0
12 if (memo[i][j] !== null) return memo[i][j]
13 const res = nums1[i] === nums2[j] ? 1 + recursion(i - 1, j - 1) : 0
14 return (memo[i][j] = res)
15 }
16
17 let res = 0
18
19 for (let i = 0; i < m; i++) {
20 for (let j = 0; j < n; j++) {
21 res = Math.max(res, recursion(i, j))
22 }
23 }
24
25 return res
26}

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Tags

leetcode

recursion

dynamic programming

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