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We might sometimes seek a tradeoff among space & time complexity. For instance, we may have to select a data structure which requires a lot of storage to reduce the computation time. Thus, the programmer has to make a judicious choice from an informed point of view. The programmer have to have some verifiable basis based on which a data structure or algorithm can be selected Complexity analysis provides such a basis.
We will learn regarding various techniques to bind the complexity function. Actually, our goal is not to count the exact number of steps of a program or the exact amount of time needed for executing an algorithm. In theoretical analysis of algorithms, this is common to estimate their complexity in asymptotic sense that means to estimate the complexity function for reasonably large length of input 'n'. Omega notation ?, big O notation, and theta notation Θ are utilized for this purpose. To measure the performance of an algorithm underlying the computer program, our approach would be depending on a concept called as asymptotic measure of complexity of algorithm. There are notations such as big O, Θ, ? for asymptotic measure of growth functions of algorithms. The most common is big-O notation. The asymptotic analysis of algorithms is frequently used since time taken to execute an algorithm varies along with the input 'n' and other factors that might differ from computer to computer and from run to run. The essences of these asymptotic notations are to bind the growth function of time complexity along with a function for sufficiently large input.
stickly binary tree
discuss the operating system under the following: MONOLITHIC SYSTEM,LAYER SYSTEM AND VIRTUAL MACHINES
Q. What is the smallest value of n such that an algorithm whose running time is 100n2 runs faster than an algorithm whose running time is 2n on the same machine. A n
The below formula is used to calculate n: n = (x * x)/ (1 - x). Value x = 0 is used to stop the algorithm. Calculation is repeated using values of x until value x = 0 is input. The
floyd warshall algorithm
Q. How do we represent a max-heap sequentially? Explain by taking a valid example. Ans: A max heap is also called as a descending heap, of size n is an almos
Draw the process flow diagram: Anand Dairy (AD) sources 150,000 litres of milk daily from large number of local villagers .The milk is collected from 4:00 AM to 6:00 am and
write a pseudocode to input the top speed (in km''s/hours) of 5000 cars output the fastest speed and the slowest speed output the average (mean) speed of all the 5000 cars answers
Have you ever thought about the handling of our files in operating system? Why do we contain a hierarchical file system? How do files saved & deleted under hierarchical directories
Q. Describe the term hashing. Explain any two usually used hash functions. Explain one method of collision resolution.
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