Same Binary Tree | LeetCode
d q, return true if the trees are equivalent, otherwise return false.Two binary trees are considered equivalent if they share the exact same structure and the nodes
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d q, return true if the trees are equivalent, otherwise return false.Two binary trees are considered equivalent if they share the exact same structure and the nodes
same tree as a given subtree.So before we solve this problem, we need to know how to check if two trees are same.IsSameTree algoFundamentally, we need to check a certain part of a tree and see if it i
ring things?We know using a hash-table we have O(1) for look up, then why study Binary Search Tree?Why is this better than hash table?Binary search tree preserves relationships, just like you would no
s height-balanced and false otherwise.A height-balanced binary tree is defined as a binary tree in which the left and right subtrees of every node differ in height by no
you how efficient your BST operations will beOperations like search, insert, delete take O(h) time, where h is heightA balanced tree with minimal depth = faster operationsIf your BST has height much
the same box.
mple.Imagine counting down from 5 to 0:for (i=5; i>=0; i=i-1) { // do something } The loop needs to:Start at 5Keep going until we hit 0Subtract 1 each timeIn assembly, we need a way to:Keep tra
that focuses on speed, memory safety, and parallelism. It was developed by Mozilla and has been gaining popularity for its ability to provide memory safety without using a garbage collector.Why Shoul
is connected to their friends, who are connected to their friends, and so on. Or think about Google Maps navigating you through city streets, finding the quickest route from your home to work. Even N
p;where stones[i] represents the weight of the ith stone.We want to run a simulation on the stones as follows:At each step we choose the two heaviest stones, with weight
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ngineer at a fast-paced AI startup, was proud of their latest code. It processed massive datasets for a new recommendation engine, simple matrix multiplications, nothing fancy.But when they ran it, th
ved a gardener named Prashant. He had two ways of planting flowers in his garden Greedy and Non-Greedy.1. The Non-Greedy WayOne day, Prashant wanted to count all the even-numbered
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nbsp;is a problem where we need to find a subsequence of three numbers in an array (nums[i], nums[j], nums[k]) such that:Indices are in order: i < j < k Values satisfy: nums[
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some problems are deceptively simple to describe but incredibly challenging to solve.One such problem is the Hamiltonian Cycle Problem, a classic puzzle that has fascinated researchers for decade
problem.Greedy algorithm makes the decision at every point choosing the local minimum or maximum depending on the optimization type.Here we want to find shortest path from S to E This is how the greed
d q, return true if the trees are equivalent, otherwise return false.Two binary trees are considered equivalent if they share the exact same structure and the nodes
same tree as a given subtree.So before we solve this problem, we need to know how to check if two trees are same.IsSameTree algoFundamentally, we need to check a certain part of a tree and see if it i
ring things?We know using a hash-table we have O(1) for look up, then why study Binary Search Tree?Why is this better than hash table?Binary search tree preserves relationships, just like you would no
1. Problem runLengthEncode
Implement a function called runLengthEncode that performs run-length encoding on a list of elements. Run-length encoding is a simple form of data compression that replaces consecutive data elements with a single data value and count.
For example:
Coming from javascript background my thought process is:
Now, we also know that in Haskell, we can do following:
defining function type
base case:
function body:
when we run this code:
visually this is what happening:
2. Problem runLengthDecode
Implement a function called runLengthDecode that decodes a run-length encoded list back into its original string.
For example:
We need to learn a replicate
let's now work on this problem 2.
3. Palindrome Checker
Palindrome Checker: Implement a function that checks if a given string is a palindrome. This will help you practice string manipulation and recursion.
4. List Compression:
List Compression: Implement a function that compresses a list by replacing consecutive duplicates with a single copy. This is similar to run-length encoding but without counting.
dropWhile:
The key point to understand is that dropWhile only operates on the beginning of the list or string. It stops as soon as it encounters an element that doesn't satisfy the condition, and then it returns the rest of the list or string from that point on, regardless of whether later elements would satisfy the condition.
Example usage:
5. Fibonacci Sequence:
Implement a function to generate the fibonacci sequence up n terms.
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