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Complexity: How do the resource needs of a program or algorithm scale (the growth of resource requirements as a function of input). In other words, what happens with the performance of an algorithm, as the size of the difficulty being solved gets larger & larger? For instance, the time & memory requirement of an algorithm that computes the sum of 1000 numbers is larger than the algorithm that computes the sum of 2 numbers.
Time Complexity: The maximum time needed through a Turing machine to execute on any input of length n.
Space Complexity: The amount of storage space needed by an algorithm varies along the size of the problem being solved out. Normally the space complexity is expressed as an order of magnitude of the size of the problem, for example (n2) means that if the size of the problem (n) doubles then the working storage (memory) needs will become four times.
Algorithm for determining strongly connected components of a Graph: Strongly Connected Components (G) where d[u] = discovery time of the vertex u throughout DFS , f[u] = f
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Define neotaxonomy. Discuss how electron microscopy can help in solving a zoological problem faced by taxonomist.
Each of the comparison in the binary search decrease the number of possible candidates where the key value can be searched by a factor of 2 as the array is divided into two halves
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write an algorithm to find the average number of occurances of MECHANIL in an english passage
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