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If the array contains all non-negative numbers, then the problem is trivial; a maximum subarray is the entire array. If the array contains all non-positive numbers, then a solution is any subarray of size 1 containing the maximal value of the array (or the empty subarray, if it is permitted).
Given the two sorted lists, the algorithm can check if an element of the first array and an element of the second array sum up to T in time (/). To do that, the algorithm passes through the first array in decreasing order (starting at the largest element) and the second array in increasing order (starting at the smallest element).
The length of is more than the length of but it is possible that not all elements in this array are used by the algorithm (in fact, if the longest increasing sequence has length then only [], …, [] are used by the
LeetCode: LeetCode has over 2,300 questions covering many different programming concepts and offers weekly and bi-weekly contests. The programming tasks are offered in English and Chinese. Project Euler [18] Large collection of computational math problems (i.e. not directly related to programming but often requiring programming skills for ...
Integer overflow can be demonstrated through an odometer overflowing, a mechanical version of the phenomenon. All digits are set to the maximum 9 and the next increment of the white digit causes a cascade of carry-over additions setting all digits to 0, but there is no higher digit (1,000,000s digit) to change to a 1, so the counter resets to zero.
The maximum coverage problem is a classical question in computer science, computational complexity theory, and operations research. It is a problem that is widely taught in approximation algorithms .
An example of a maximum cut. In a graph, a maximum cut is a cut whose size is at least the size of any other cut. That is, it is a partition of the graph's vertices into two complementary sets S and T, such that the number of edges between S and T is as large as possible. Finding such a cut is known as the max-cut problem.
The following C subroutine max() returns the maximum value in its argument array a[], provided its length n is at least 1. Comments are provided at lines 3, 6, 9, 11, and 13. Each comment makes an assertion about the values of one or more variables at that stage of the function.