MindFount Infotech Sde1 Interview Questions and Answers

NP hardness refers to the difficulty of solving a problem in non-deterministic polynomial time.

• NP-hard problems are some of the most difficult problems in computer science.

• They cannot be solved in polynomial time by any known algorithm.

• Examples include the traveling salesman problem and the knapsack problem.

A reference variable is a variable that holds the memory address of an object, while an actual reference is the object itself.

• A reference variable is declared with a specific type and can only refer to objects of that type.

• An actual reference is the object itself, which can be accessed and manipulated using the reference variable.

• Changing the value of a reference variable does not affect the original object, but changi...read more

The 0-1 Knapsack problem involves maximizing value within a weight limit using items that can either be included or excluded.

• Dynamic Programming approach is commonly used to solve this problem.

• Each item has a weight and a value; you cannot take fractional items.

• Example: If you have items with weights [1, 2, 3] and values [10, 15, 40], and a capacity of 6, the maximum value is 55.

• The solution involves creating a table t...read more

When we type an URL, the browser sends a request to the server hosting the website and retrieves the corresponding webpage.

• The browser parses the URL to extract the protocol, domain, and path.

• It resolves the domain name to an IP address using DNS.

• The browser establishes a TCP connection with the server.

• It sends an HTTP request to the server.

• The server processes the request and sends back an HTTP response.

• The browser re...read more

Implementation of LRU cache using a doubly linked list and a hash map.

• LRU (Least Recently Used) cache is a data structure that stores a fixed number of items and evicts the least recently used item when the cache is full.

• To implement LRU cache, we can use a doubly linked list to maintain the order of items based on their usage frequency.

• We can also use a hash map to store the key-value pairs for quick access and retrie...read more

Explaining page replacement algorithms like FIFO and LRU using a given page access sequence.

• FIFO (First-In-First-Out): Replaces the oldest page in memory.

• Example: Access sequence [1, 2, 3, 1, 2, 4] with 3 frames results in [1, 2, 4].

• LRU (Least Recently Used): Replaces the page that hasn't been used for the longest time.

• Example: Access sequence [1, 2, 3, 1, 2, 4] with 3 frames results in [2, 3, 4].

• Optimal: Replaces the ...read more

Indexing in DBMS is a technique to improve query performance by creating a data structure that allows faster data retrieval.

• Indexing is used to speed up data retrieval operations in a database.

• It involves creating a separate data structure that maps the values of a specific column to their corresponding records.

• This data structure is called an index.

• Indexes are typically created on columns that are frequently used in s...read more

Given a list of process IDs and their corresponding parent process IDs, print the IDs of all processes that are children of a specific process ID, and recursively kill all their children.

• Iterate through the list of process IDs and parent process IDs

• Check if the current process ID is the one to be killed

• If yes, recursively find and print all its children

• If a child has further children, recursively kill them as well

Search for an element in a rotated sorted array.

• Use binary search to find the pivot point where the array is rotated.

• Compare the target element with the first element of the array to determine which half to search.

• Perform binary search on the selected half to find the target element.

• Time complexity: O(log n), Space complexity: O(1).

Find the first non-repeating character in a continuous character stream.

• Use a hash table to keep track of character frequency.

• Iterate through the stream and check if the current character has a frequency of 1.

• If yes, return the character as the first non-repeating character.

• If no non-repeating character is found, return null or a default value.