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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.
Define Hashing. Store the following values in a hash table of table size 11 using division method: 25, 42, 96, 101, 102, 162, and 197. In case of collision, use other hash functio
Game trees An interesting application of trees is the playing of games such as tie-tac-toe, chess, nim, kalam, chess, go etc. We can picture the sequence of possible moves by m
Run time complexity of an algorithm is depend on
The controversy of RISC versus CISC never ends. Suppose that you represent an advocate for the RISC approach; write at least a one-page critic of the CISC approach showing its disa
In this unit, the following four advanced data structures have been practically emphasized. These may be considered as alternative to a height balanced tree, i.e., AVL tree.
In worst case Quick Sort has order O (n 2 /2)
What is tha flow chart of algorithm
Ask question find frequency count of function- {for(i=1;i {for(j=1;j {for(k=1;k } } }
prove that n/100=omega(n)
Write an algorithm for binary search. Algorithm for Binary Search 1. if (low> high) 2. return (-1) 3. Mid = (low + high)/2 4. if ( X = = a[mid]) 5. return (mid); 6.
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