Table of Contents

## How do you implement DFS?

The DFS algorithm works as follows:

- Start by putting any one of the graph’s vertices on top of a stack.
- Take the top item of the stack and add it to the visited list.
- Create a list of that vertex’s adjacent nodes.
- Keep repeating steps 2 and 3 until the stack is empty.

## How does DFS work on a graph?

Depth-first search (DFS) is an algorithm for traversing or searching tree or graph data structures. The algorithm starts at the root node (selecting some arbitrary node as the root node in the case of a graph) and explores as far as possible along each branch before backtracking.

**How do you implement a depth first search in python?**

Explanation

- It first checks if the current node is unvisited – if yes, it is appended in the visited set.
- Then for each neighbor of the current node, the dfs function is invoked again.
- The base case is invoked when all the nodes are visited. The function then returns.

### Does BFS work on directed graphs?

For directed graphs, too, we can prove nice properties of the BFS and DFS tree that help to classify the edges of the graph. For BFS in directed graphs, each edge of the graph either connects two vertices at the same level, goes down exactly one level, or goes up any number of levels.

### What is BFS and DFS with example?

BFS stands for Breadth First Search. DFS stands for Depth First Search. 2. BFS(Breadth First Search) uses Queue data structure for finding the shortest path. BFS can be used to find single source shortest path in an unweighted graph, because in BFS, we reach a vertex with minimum number of edges from a source vertex.

**Does BFS visit every vertex?**

Put differently, BFS runs in linear time in the size of the graph. Proof: It explores every vertex once.

#### Can a directed graph be disconnected?

An edgeless graph with two or more vertices is disconnected. A directed graph is called weakly connected if replacing all of its directed edges with undirected edges produces a connected (undirected) graph.

#### Why is BFS V E?

3 Answers. Overall, BFS accesses (and processes) each edge constant times (twice actually; we assume an undirected graph), costing O(E) total time in edge processing. The overhead for initialization is O(V). Thus the total running time of BFS is O(V+E).

**What is the purpose of running a BFS on a graph?**

Breadth-first search (BFS) is an important graph search algorithm that is used to solve many problems including finding the shortest path in a graph and solving puzzle games (such as Rubik’s Cubes).

## Why is DFS v E?

Each vertex is marked as visited right after DFS-VISIT starts in them. Since it is impossible for a vertex to be visited twice, there goes your O(V) part. DFS-VISIT iterates over the adjacency list of each vertex it visits, so in the worst case it iterates over all edges. There goes O(E).

## Why DFS time complexity is V E?

The time complexity of DFS if the entire tree is traversed is O(V) where V is the number of nodes. So, the time complexity in this case is O(V) + O(E) = O(V + E). For an undirected graph, each edge appears twice. Once in the adjacency list of either end of the edge.

**Is DFS faster than BFS?**

BFS, stands for Breadth First Search. DFS, stands for Depth First Search. BFS uses Queue to find the shortest path. DFS is faster than BFS.

### Does DFS revisit nodes?

1 Answer. Depth first search will put a node into the stack only once. A node will not enter the stack if and only if it is not part of the connected component involving the DFS start vertex. This only matters for graphs made out of disjoint connected components and not for connected graphs.

### Which has lowest worst case complexity?

Answer is C. Worst case complexity of merge sort is O(nlogn).

**Which has lowest run time complexity?**

This time complexity is defined as a function of the input size n using Big-O notation. n indicates the input size, while O is the worst-case scenario growth rate function….What is time complexity?

Big O Notation | Name | Example(s) |
---|---|---|

O(n2) | Quadratic | # Duplicate elements in array **(naïve)**, # Sorting array with bubble sort |

#### Which sorting technique has the least worst case?

ANSWER: Merge sort The merge sort uses the weak complexity their complexity is shown as O(n log n).

#### What is the number of swaps required to sort in the worst case?

Answer: Worst case of number of swaps is n-1.

**What is the best case efficiency of bubble sort in improvised version?**

Discussion Forum

Que. | What is the best case efficiency of bubble sort in the improvised version? |
---|---|

b. | O(logn) |

c. | O(n) |

d. | O(n^2) |

Answer:O(n) |

## Is quick sort stable?

No

## Which sorting algorithm finds the largest number first?

In a selection sort, the first process in the algorithm is to find the data element that has the largest value.

- Since 5 is not larger than 55, max and maxpos are left alone.
- At this point the array looks like this:
- The process is repeated by changing the lead position to be the second element.

**Which function finds the largest number in a range?**

Example

A | |
---|---|

Formula | Description (Result) |

=MIN(A2:A7) | Smallest number in the range (0) |

=MAX(A2:A7) | Largest number in the range (27) |

=SMALL(A2:A7, 2) | Second smallest number in the range (4) |

### How do you find the largest and second largest number in an array?

A simple way to find the largest and second-largest number is that sort the array in descending order and pick its first and second elements. Its first element will be the largest number and the second number will be the second-largest number. The time complexity of this solution is O(n log n).

### How do you find the maximum and minimum of an array?

The function getresult( int arr[],int n) is to find the maximum and minimum element present in the array in minimum no. of comparisons. If there is only one element then we will initialize the variables max and min with arr[0] . For more than one element, we will initialize max with arr[1] and min with arr[0].

**How do you find the 2nd maximum element in an array?**

Find 2nd Largest Number in Array using Collections

- import java.util.*;
- public class SecondLargestInArrayExample2{
- public static int getSecondLargest(Integer[] a, int total){
- List list=Arrays.asList(a);
- Collections.sort(list);
- int element=list.get(total-2);
- return element;
- }

#### What is the number 1000000000000000000000000?

Some Very Big, and Very Small Numbers

Name | The Number | Symbol |
---|---|---|

septillion | 1,000,000,000,000,000,000,000,000 | Y |

sextillion | 1,000,000,000,000,000,000,000 | Z |

quintillion | 1,000,000,000,000,000,000 | E |

quadrillion | 1,000,000,000,000,000 | P |

#### Is Tree 3 the biggest number?

What is TREE(3)? It’s a number. An enormous number beyond our ability to express with written notation, beyond what we could even begin to comprehend, bigger than the notoriously gargantuan Graham’s number. We know TREE(3) exists, and we know it’s finite, but we do not know what it is or even how many digits there are.