I am developing a simple tile-based 2D game. I have a level, populated with objects that can interact with the tiles and with each other. Checking c开发者_StackOverflowollision with the tilemap is rat
Most people with a degree in CS will certainly know what Big O stands for. It helps us to measure how well an algorithm scales.
Given n bins of infinite capacity, I want to pack m items into them (each with a specific weight), whilst minimizing the weight of the heaviest bin.
sum = 0; for(int i = 0; i < N; i++) for(int j = i; j >= 0; j--) sum++; From what I understand, the first line is 1 operation, 2nd line is (i+1) operations, 3rd line is (i-1) operations, and 4t
I\'m开发者_StackOverflow社区 looking at the article on wikipdia for this algorithm, and I see two seemingly contradictory statements:
Few days ago I was working on interval graphs to solve the known problem of resource allocation, as we know there is a greedy approach that solves this problem (chromatic number) in polynomial time an
i have learned that a program is measured by it\'s complexity - i mean by Big O Notation. why don\'开发者_如何学Ct we measure it by it\'s absolute running time?
I\'m looking into using compression as a way to measure the relation of a document to a corpus of documents. In doing so I\'ve found a strange result when using bzip2; len(compress(corpus)) > len(comp
let\'s say i have an array, size 40. and the element im looking for is in position 38. having a simple loop, it will 开发者_如何学JAVAtake 38 steps right?
I am trying to find the best way to solve the following problem. By best way I mean less complex. As an input a list of tuples (start,length) such:
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