Tip 1: Practice at least 250 questions.
Tip 2: Do at least 2 projects.
Tip 3: Practice company's past OA questions, if available.
Tip 1: Have some projects on your resume.
Tip 2: Do not include false information on your resume.



Binary Search for Full Rounds: The total number of candies k can be very large (1014). Instead of simulating, use binary search to find the maximum number of full rounds R you can complete. A round is "full" if you can give 1 candy to every animal that still needs one.
Calculate Remaining Candies: After R full rounds, some animals are "finished" (if ai≤R). Subtract the candies eaten in these R rounds from k.
Final Simulation: With the remaining k′ candies (where k′< number of active animals), iterate through the animals one last time. If an animal still needs candies, give it one and decrement k′. Once k′ reaches zero, the current animal is finished; output the indices of all other animals that still need more than R candies (or R+1 if they were already passed in this last partial round).



Generate Candidate Palindromes: A binary palindrome of length L is determined by its first ⌈L/2⌉ bits. Since N can be up to 1018 (approx 60 bits), generate palindromes of length len(N)−1, len(N), and len(N)+1.
Constructing from Prefix: For a fixed length L, take the first half of N's binary representation. Create three palindromes by:
Using the prefix as is.
Subtracting 1 from the prefix.
Adding 1 to the prefix.
(This covers the closest values numerically).
Find Minimum Difference: Convert these binary candidates back to decimals. Calculate the absolute difference with N and pick the one with the smallest difference.



A subtree of a tree T is a tree S consisting of a node in T and all of its descendants in T. The subtree corresponding to the root node is the entire tree. For better understanding, refer to the image below:-

1. The tree will always be rooted at 0.
2. You can return the count of nodes in any order.
3. The root of any subtree is also counted in the subtree thus the count of nodes in a subtree rooted at a leaf node is
4. You can return the numbers in any order.
Identify Heavy/Light Children: For each node, find the "heavy" child (the child with the largest subtree size). All other children are "light."
The "DSU on Tree" Logic:
Recursively solve for all light children but clear their data (e.g., map or frequency array) after solving.
Recursively solve for the heavy child and keep its data.
Iterate through all light children again, adding their subtree values into the heavy child's existing data.
Answer the Query: Now the data structure contains all the info for node u's subtree. Store the answer for node u. By keeping the heavy child's data, you ensure each node is added to a data structure at most O(logN) times.

Here's your problem of the day
Solving this problem will increase your chance to get selected in this company
Which method is called when an object is destroyed in Java?