- What are the main criteria to judge an algorithm?
- What is O n complexity?
- What is the average case time complexity of MIN MAX algorithm?
- Which notation is used for average case analysis?
- What is the fastest sorting algorithm?
- What is best case time complexity?
- What do you mean by best case efficiency?
- What happens when quicksort algorithm performs its worst case?
- What is best algorithm case?
- How do you calculate average case efficiency?
- What is average case running time?
- What are two main measures for the efficiency of an algorithm?
- What is worst case of an algorithm?
- Is Big O notation the worst case?
- How do you find the worst case and best case of an algorithm?

## What are the main criteria to judge an algorithm?

All algorithms must satisfy the following criteria:Zero or more input values.One or more output values.Clear and unambiguous instructions.Atomic steps that take constant time.No infinite sequence of steps (help, the halting problem)Feasible with specified computational device..

## What is O n complexity?

O(n) represents the complexity of a function that increases linearly and in direct proportion to the number of inputs. This is a good example of how Big O Notation describes the worst case scenario as the function could return the true after reading the first element or false after reading all n elements.

## What is the average case time complexity of MIN MAX algorithm?

The time complexity of minimax is O(b^m) and the space complexity is O(bm), where b is the number of legal moves at each point and m is the maximum depth of the tree.

## Which notation is used for average case analysis?

The notation Ω(n) is the formal way to express the lower bound of an algorithm’s running time. It measures the best case time complexity or the best amount of time an algorithm can possibly take to complete.

## What is the fastest sorting algorithm?

QuicksortThe time complexity of Quicksort is O(n log n) in the best case, O(n log n) in the average case, and O(n^2) in the worst case. But because it has the best performance in the average case for most inputs, Quicksort is generally considered the “fastest” sorting algorithm.

## What is best case time complexity?

The best-case complexity of the algorithm is the function defined by the minimum number of steps taken on any instance of size n. It represents the curve passing through the lowest point of each column.

## What do you mean by best case efficiency?

Best case efficiency. is the minimum number of steps that an algorithm can take any collection of data values. Average case efficiency. – the efficiency averaged on all possible inputs.

## What happens when quicksort algorithm performs its worst case?

When Does the Worst Case of Quicksort Occur? elements. Similarly, when the given input array is sorted reversely and we choose the rightmost element as the pivot element, the worst case occurs. Again, in this case, the pivot elements will split the input array into two unbalanced arrays.

## What is best algorithm case?

Best case is the function which performs the minimum number of steps on input data of n elements. Worst case is the function which performs the maximum number of steps on input data of size n. Average case is the function which performs an average number of steps on input data of n elements.

## How do you calculate average case efficiency?

Average-case time complexity is a less common measure:Let T1(n), T2(n), … be the execution times for all possible inputs of size n, and let P1(n), P2(n), … be the probabilities of these inputs.The average-case time complexity is then defined as P1(n)T1(n) + P2(n)T2(n) + …

## What is average case running time?

The average-case running time of an algorithm is an estimate of the running time for an “average” input. Computation of average-case running time entails knowing all possible input sequences, the probability distribution of occurrence of these sequences, and the running times for the individual sequences.

## What are two main measures for the efficiency of an algorithm?

1 . Two main measures for the efficiency of an algorithm areProcessor and memory.Complexity and capacity.Time and space.Data and space.

## What is worst case of an algorithm?

In computer science, the worst-case complexity (usually denoted in asymptotic notation) measures the resources (e.g. running time, memory) that an algorithm requires given an input of arbitrary size (commonly denoted as n or N). It gives an upper bound on the resources required by the algorithm.

## Is Big O notation the worst case?

Worst case — represented as Big O Notation or O(n) Big-O, commonly written as O, is an Asymptotic Notation for the worst case, or ceiling of growth for a given function. It provides us with an asymptotic upper bound for the growth rate of the runtime of an algorithm.

## How do you find the worst case and best case of an algorithm?

In the simplest terms, for a problem where the input size is n:Best case = fastest time to complete, with optimal inputs chosen. For example, the best case for a sorting algorithm would be data that’s already sorted.Worst case = slowest time to complete, with pessimal inputs chosen. … Average case = arithmetic mean.