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In this approach, we use an auxiliary 'visited' array to keep track of the elements that have already been included in any set s[k]. For each unvisited element at index i, we keep iterating through the sequence by accessing nums[nums[i]] until we encounter an element already visited. Each time we reach an unvisited element, we mark it as visited, and increment the length of the current sequence. We keep track of the longest length among all sequences generated from each starting index.
Time Complexity: O(N), where N is the number of elements in the array, as each element is visited at most once.
Space Complexity: O(N) due to the additional 'visited' array.
1var arrayNesting = function(nums) {
2 let visited = new Array(nums.length).fill(false);
3 let maxLength = 0;
4 for (let i = 0; i < nums.length; i++) {
5 if (!visited[i]) {
6 let start = i, length = 0;
7 while (!visited[start]) {
8 visited[start] = true;
9 start = nums[start];
10 length++;
11 }
12 maxLength = Math.max(maxLength, length);
13 }
14 }
15 return maxLength;
16};
17
18console.log(arrayNesting([5, 4, 0, 3, 1, 6, 2]));In JavaScript, the length of each sequence is tracked as we iterate over each unvisited element. Storing this data in an array allows the program to avoid redundancy but track the highest nesting from iterative loops starting at each index, ultimately giving us the sequence's length output.
This approach minimizes space usage by modifying the input array itself as a marker of visited nodes. By setting each visited position to a sentinel value (e.g., -1 or a number outside the expected range), we can achieve the same iterative closure tracking. We simply iterate over each number and trace the sequence until we circle back to a marked node. This is an improvement on memory constraints when needing to handle particularly large datasets.
Time Complexity: O(N), executing a linear pass through the nodes.
Space Complexity: O(1), modifying input without auxiliary space.
JavaScript carries out position work by utilizing the derived in-situ signifiers within the main sequence of values, safely distinguishing completed cycles post-processing maximizations. With only required steps followed, this method embodies a concise, purposeful strategy on avoiding uniform steps repeated ambiguously.