{"id":2284,"date":"2020-06-15T03:38:19","date_gmt":"2020-06-15T03:38:19","guid":{"rendered":"https:\/\/blog.prepbytes.com\/?p=2284"},"modified":"2022-05-23T11:19:56","modified_gmt":"2022-05-23T11:19:56","slug":"consecutive-permutation","status":"publish","type":"post","link":"https:\/\/prepbytes.com\/blog\/consecutive-permutation\/","title":{"rendered":"Consecutive Permutation"},"content":{"rendered":"

\"\"<\/p>\n

Concepts Used<\/h3>\n
\n

Segment Trees<\/p>\n<\/blockquote>\n

Difficulty Level<\/h3>\n
\n

Hard<\/p>\n<\/blockquote>\n

Problem Statement :<\/h3>\n
\n

Given an array of N<\/code> unique elements and Q<\/code> queries. In each query, we are given two values l,r<\/code>. We want to know if there is a permutation of all the integers in this range such that in that permutation all the elements are consecutive. Print Yes if such a permutation exists else No.<\/p>\n<\/blockquote>\n

<\/strong><\/u><\/a><\/p>\n

Solution Approach :<\/h3>\n

Introduction<\/strong> :<\/p>\n

\n

We have to find where the array elements in the given range is
\nconsecutive or not. We can solve this problem using brute force approach or using segment tree. Basic idea is to keep track of the lowest and highest values of the array within the given range now the difference between these values is equal to the difference between the ranges then we can say the array elements are consecutive, else not.<\/p>\n<\/blockquote>\n

Method 1 (Brute force)<\/strong>:<\/p>\n

\n

We can calculate the minimum and maximum values within the given range in linear time for each query by sorting the array in increasing order. Then check whether the difference between these values and the given range is same or not.<\/p>\n<\/blockquote>\n

Method 2 (Segment Tree)<\/strong>:<\/p>\n

\n

As the number of queries and array size is too large for linear search in every query, we will use segment tree<\/strong> to solve this problem.
\nA Segment Tree<\/strong> is a data structure which allows answering range queries very effectively over a large input. Each query takes logarithmic time. Range queries includes sum over a range, or finding a minimum value over a given range etc. Query be of any type we can use segment trees and modify it accordingly.
\nLeaf nodes of the tree stores the actual array values and intermediate nodes stores the information of subarrays with is require to solve the problem. Lets say if we have to find a sum between different ranges, so now the intermediate nodes will store the sum of the current subarray. We fill the nodes by recursively calling left and right subtree (dividing into segements), untill there is a single element left, which can be directly assigned the value of the array. Array representation of the tree is used to represent segment tree, where (i*2)+1<\/code> represents the left node and (i*2)+2<\/code> represents right node, parent will be represented by (i-1)\/2<\/code> for every index i<\/code>.
\nWe will construct<\/strong> two segment trees, one for storing minimum values and other to store maximum values of the subarrays.
\nWe begin with the original array and dividing it into two halves (left and right), untill there is a single element left (leaf) which can directly be filled with a[i]<\/code> for any index i<\/code>. Now for every range say l<\/code> to r<\/code>, we will store the minimum and maximum values of the current range in the node in first and second tree respectively.
\nNow that our tree is constructed, we will answer queries<\/strong> (minimum\/maximum of the given range). The queries can be of 3<\/code> types: <\/p>\n

    \n
  1. The range of the tree exactly matches with the query, in this case we will return the value stored in this node.<\/li>\n
  2. The range either belongs to the left<\/code> or right<\/code> node, in this case we will make two recursive calls for left<\/code> and right<\/code> subtrees respectively.<\/li>\n
  3. The range overlaps with two of more ranges, in this case we are forced to go to the lower levels of both the subtrees and find the gcd of the range which fits the current range and finally return the minimum\/maximum of the values returned by both subtrees.
    \nNow after retrieving the minimum and maximum values within the range from both segment trees we will check whether the difference max - min +1<\/code> is equal to the range gap r-l+1<\/code>. Since we are assuming array has distinct values this difference must be equal if the array elements are consecutive.<\/li>\n<\/ol>\n<\/blockquote>\n

    \"\"<\/p>\n

    Algorithms :<\/h3>\n

    construct_min()<\/strong>:<\/p>\n

    \n
      \n
    • if the current node is a leaf (subarray contains single elemnt), assign the value directly, (tree[curr]= arr[l])<\/code>.<\/li>\n
    • break the tree into two halves by recursively calling for left and right subtree, construct(l,mid)<\/code> and construct(mid+1,r)<\/code><\/li>\n
    • fill the current node with the minimum of left & right node. (tree[curr] = min(LeftSubtree , RightSubtree)<\/code>.<\/li>\n<\/ul>\n<\/blockquote>\n

      construct_max()<\/strong>:<\/p>\n

      \n
        \n
      • if the current node is a leaf (subarray contains single elemnt), assign the value directly, (tree[curr]= arr[l])<\/code>.<\/li>\n
      • break the tree into two halves by recursively calling for left and right subtree, construct(l,mid)<\/code> and construct(mid+1,r)<\/code><\/li>\n
      • fill the current node with the maximum of left & right node. (tree[curr] = max(LeftSubtree , RightSubtree)<\/code>.<\/li>\n<\/ul>\n<\/blockquote>\n

        RMQ_min()<\/strong>:<\/p>\n

        \n
          \n
        • if range is within the current range, return the value stored in node.<\/li>\n
        • if current range is outside the boundaries, return -1<\/code>.<\/li>\n
        • else return the min of left & right subtrees.<\/li>\n<\/ul>\n<\/blockquote>\n

          RMQ_max()<\/strong>:<\/p>\n

          \n
            \n
          • if range is within the current range, return the value stored in node.<\/li>\n
          • if current range is outside the boundaries, return -1<\/code>.<\/li>\n
          • else return the max of left & right subtrees.<\/li>\n<\/ul>\n<\/blockquote>\n

            Complexity Analysis :<\/h3>\n
            \n

            In the brute force approach the time complexity<\/strong> for sorting is O(nlogn)<\/code> and total time complexity will be O(Q*nlogn)<\/code>.
            \nIn segment tree, preprocessing time is O(n)<\/code> for each tree and worst time to for range minimum\/maximum query is equivalent to the height of the tree.
            \nThe space complexity<\/strong> is O(n)<\/code> to store the segment tree.<\/p>\n<\/blockquote>\n

            Solutions:<\/h3>\n

            \t\t\t\t\t\t