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What do you mean by complexity of an algorithm?
The complexity of an algorithm M is the function f(n) which gives the running time and/or storage space need of the algorithm in terms of the size n of the input data. Frequently, the storage space needed by an algorithm is simply a multiple of the data size n. Thus, the term "complexity" shall refer to the running time of the algorithm.
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How will you represent a max-heap sequentially? Max heap, also known as the descending heap, of size n is an almost complete binary tree of n nodes such that the content of eve
State the complex reallocation procedure Some languages provide arrays whose sizes are established at run-time and can change during execution. These dynamic arrays have an in
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Q. What is the need of using asymptotic notation in the study of algorithm? Describe the commonly used asymptotic notations and also give their significance.
Q. Write an algorithm that counts number of nodes in a linked list. A n s . Algo rithm to Count No. of Nodes in Linked List C
Explain in detail about the Ruby arrays Ruby arrays have many interesting and powerful methods. Besides indexing operations which go well beyond those discussed above, arrays h
* Initialise d & pi* for each vertex v within V( g ) g.d[v] := infinity g.pi[v] := nil g.d[s] := 0; * Set S to empty * S := { 0 } Q := V(g) * While (V-S)
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