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Complexity is the rate at which the needed storage or consumed time rise as a function of the problem size. The absolute growth based on the machine utilized to execute the program, the compiler utilized to construct the program, and several other factors. We would like to have a way of defining the inherent complexity of a program (or piece of a program), independent of machine/compiler considerations. It means that we have to not attempt to describe the absolute time or storage needed. We have to instead concentrate on a "proportionality" approach, expressing the complexity in terms of its relationship to some known function. This kind of analysis is known as asymptotic analysis. It might be noted that we are dealing with complexity of an algorithm not that of a problem. For instance, the simple problem could have high order of time complexity & vice-versa.
A B-tree of minimum degree t can maximum pointers in a node T pointers in a node.
An undirected graph G with n vertices and e edges is shown by adjacency list. What is the time required to generate all the connected components? O (e+n)
#question.explain different types of errors in data transmission.
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So far, we now have been concerned only with the representation of single stack. What happens while a data representation is required for several stacks? Let us consider an array X
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Q.1 Compare two functions n 2 and 2 n for various values of n. Determine when second becomes larger than first. Q.2 Why do we use asymptotic notation in the study of algorit
W h at are the different ways by which we can represent graph? Represent the graph drawn below using those ways. T he d iff e r e nt w a y s by
Write a procedure (make-stack) that produces independent stack objects, using a message-passing style, e.g. (define stack1 (make-stack)) (define stack2 (make-stack)) W
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