SDE - Intern

1. Start by initializing a stack data structure, which will help in keeping track of the opening braces and their positions.

2. Next, iterate through each character of the input string and check if it is an opening brace ('{' or '['). If it is, push it onto the stack along with its position.

3. If the character is a closing brace ('}' or ']'), check if the stack is empty. If it is, return False as there is no matching opening brace.

4. If the stack is not empty, pop the top element from the stack and check if it matches the current closing brace. If it does not match, return False as the brace is not in the correct order.

5. Repeat steps 3-4 until the end of the string is reached.

6. After the iteration, check if the stack is empty. If it is, return True as all braces are in the correct order. If it is not empty, return False as there is a brace with no matching partner.

7. Additionally, add checks to handle edge cases like an empty input string, an input string with no braces, or a mismatched combination of braces like '[}', '{]', etc.

8. Test the program with various input strings to ensure it works correctly in all cases.

One common problem in computer science is to check whether a pair exists in a given array with a specific sum, which can be approached using techniques like a two-pointer algorithm, hashing, or sorting.

1. Create an empty hash table.
2. Traverse the array, and for each element:
i. Compute the difference between the given sum and the current element.
ii. Check if the difference exists in the hash table. If it does, then a pair with the given sum exists, and we can return true.
iii. If the difference does not exist in the hash table, add the current element to the hash table.
3. If the traversal is complete and no pair with the given sum has been found, return false.
4. Repeat steps 2 and 3 for all elements in the array.
5. Return the final result indicating whether a pair with the given sum exists in the array.

1. Initialize two variables max_so_far and max_ending_here to 0.
2. Traverse the array arr from left to right, and for each element arr[i]:
Add arr[i] to max_ending_here.
If max_ending_here is negative, reset it to 0.
If max_ending_here is greater than max_so_far, set max_so_far to max_ending_here.
3. Return max_so_far.

This algorithm is called Kadane's algorithm and has a time complexity of O(N), where N is the size of the input array.