SDE - 1

This was a pretty standard Binary Search Question and I had solved this question before on platforms like LeetCode and CodeStudio . I was asked this question to test my implementation skills and how well do I handle Edge Cases .

Approach :
1) The idea is to find the pivot point, divide the array in two sub-arrays and perform binary search.
2) The main idea for finding pivot is – for a sorted (in increasing order) and pivoted array, pivot element is the only element for which next element to it is smaller than it.
3) Using the above statement and binary search pivot can be found.
4) After the pivot is found out divide the array in two sub-arrays.
5) Now the individual sub – arrays are sorted so the element can be searched using Binary Search.

TC : O(Log(N))
SC : O(1)

This problem can be solved using hashing. The idea is to traverse the tree in an inorder fashion and insert every node’s value into a set. Also check if, for any node, the difference between the given sum and node’s value is found in the set, then the pair with the given sum exists in the tree.
Time Complexity :O(n).

Recursion can be used to solve this problem. We reverse every group of k linked list nodes and attach it to the previous group. 
Steps :
1) The first step is to check whether the Head is NULL or Not, if its NULL then we can directly return NULL,
2) If the Head is not NULL, then we need to check the length of Linked List starting from current Head.
3) If the length is less than k , then there is no need to reverse it and hence we can directly return head,
4) Else if its a multiple of K, then we have to reverse the K elements starting from current Head. While reversing keep track of the next node and previous node. 
5) We will follow the same steps for the rest of the elements Recursively and link the two sub-lists. 
Time Complexity : O(n)
Auxiliary Space : O(n/k)

Recursion can be used to reverse a stack. In this approach, we pop the top element from the given stack and recursively call another instance of the same function. When this child function returns to the parent function, append the popped element to the bottom of the stack. For this, two recursive functions can be used: reverseStack() and insertAtBottom(). 

reverseStack():
It checks if the stack is empty or not. The top element is popped out and stored in the element variable if the stack is not empty. We then call reverseStack() function again on the updated stack. When this child function returns, we call the helper function insertAtBottom().

insertAtBottom(): 
It recursively inserts an element at the bottom of a stack. If the stack is empty, it simply pushes the element else; the top element is popped out and stored in the topElement variable. Then insertAtBottom() is called again on the updated stack. When this child function returns, it pushes the topElement back in the stack.

Time Complexity: O(N²) : Two recursive functions are there in which the first function is calling itself recursively and the second function in each call. Also, the second function is recursively called.
Space Complexity: O(N) : The recursive program uses a memory of O(N) to store the function call stack.

"The cloud" refers to servers that are accessed over the Internet, and the software and databases that run on those servers. Cloud servers are located in data centers all over the world. By using cloud computing, users and companies do not have to manage physical servers themselves or run software applications on their own machines.
The cloud enables users to access the same files and applications from almost any device, because the computing and storage takes place on servers in a data center, instead of locally on the user device.

1) Back-up and restore data
Once the data is stored in the cloud, it is easier to get back-up and restore that data using the cloud.

2) Improved collaboration
Cloud applications improve collaboration by allowing groups of people to quickly and easily share information in the cloud via shared storage.

3) Excellent accessibility
Cloud allows us to quickly and easily access store information anywhere, anytime in the whole world, using an internet connection. An internet cloud infrastructure increases organization productivity and efficiency by ensuring that our data is always accessible.

4) Low maintenance cost
Cloud computing reduces both hardware and software maintenance costs for organizations.

5) Mobility
Cloud computing allows us to easily access all cloud data via mobile.

6) Data security
Data security is one of the biggest advantages of cloud computing. Cloud offers many advanced features related to security and ensures that data is securely stored and handled.

Security and Privacy
Security and Privacy of information is the biggest challenge to cloud computing. Security and privacy issues can be overcome by employing encryption, security hardware and security applications.

Portability
This is another challenge to cloud computing that applications should easily be migrated from one cloud provider to another. There must not be vendor lock-in. However, it is not yet made possible because each of the cloud provider uses different standard languages for their platforms.

Interoperability
It means the application on one platform should be able to incorporate services from the other platforms. It is made possible via web services, but developing such web services is very complex.

Computing Performance
Data intensive applications on cloud requires high network bandwidth, which results in high cost. Low bandwidth does not meet the desired computing performance of cloud application.