The trick is to figure out a way to categorize the possible solutions and come up with a linear-time constant-space solution for each. Consider the three ranges X = (0,2/3), Y = [2/3,1], Z = (1,2). At most one value can come from Z (if two values came from Z, then the sum would exceed … Read more
MergeSort time Complexity is O(nlgn) which is a fundamental knowledge. Merge Sort space complexity will always be O(n) including with arrays. If you draw the space tree out, it will seem as though the space complexity is O(nlgn). However, as the code is a Depth First code, you will always only be expanding along one … Read more
Correct, the extra space are the log(n) stack frames. From the Wikipedia article of Quicksort: There is a more complex version which […] can achieve the complete sort using O(log n) space (not counting the input) on average (for the call stack). While you could implement quicksort iteratively (i.e., using a loop instead of recursion), … Read more
A useful way to approach these types of problems is by thinking of the recursion tree. The two features of a recursive function to identify are: The tree depth (how many total return statements will be executed until the base case) The tree breadth (how many total recursive function calls will be made) Our recurrence … Read more
To answer your question, if you have a traversal algorithm for traversing the list which allocate a single pointer to do so, the traversal algorithms is considered to be of O(1) space complexity. Additionally, let’s say that traversal algorithm needs not 1 but 1000 pointers, the space complexity is still considered to be O(1). However, … Read more