SDE - 1

To solve this problem using dynamic programming, I used an array to store the longest increasing subsequence ending at each index of the input array. The length of the longest increasing subsequence ending at the current index can be determined by comparing the current value to the previous values in the array and taking the maximum value.

This problem is a classic example of dynamic programming. It has a time complexity of O(n^2) and space complexity of O(n).

This problem can be solved using dynamic programming by creating a 2-dimensional array to store the minimum number of operations needed to transform the first string up to the index i into the second string up to the index j. The value at each index can be determined by considering the case of a substitution, deletion, or insertion.

The time complexity for this problem is O(nm) where n is the length of string1 and m is the length of string2 and space complexity is O(nm) as well.

To solve this problem, you can use a hash map to store the anagrams. The key of the map should be a string representing the sorted characters of the original string and the value should be a vector of strings that are anagrams of the key.

You iterate through the input array, for each string, sort the characters and use the sorted string as a key to check if it already exists in the map. If it does, add the original string to the corresponding value vector, if not, create a new key-value pair in the map with the sorted string as the key and a new vector containing the original string as the value.

This problem has a time complexity of O(nm log m) where n is the size of the input array and m is the length of the longest string in the input array, it's because of sorting each string, the space complexity is O(nm) where n is the size of the input array and m is the length of the longest string in the input array.

CODE:
vector> groupAnagrams(vector& strs) {
unordered_map> map;
for (string s : strs) {
string key = s;
sort(key.begin(), key.end());
map[key].push_back(s);
}
vector> res;
for (auto p : map) {
res.push_back(p.second);
}
return res;
}


it might feel like an easy problem , but believe me it wasn't , I tried to give an easier understating of the question here , but interviewer uses tricky situations to ask this question.

This problem can be solved using a combination of algorithms such as divide and conquer, sorting and brute force. The divide and conquer approach is more efficient as it reduces the number of points to consider, sorting is used to order the points by their x or y-coordinates and brute force is used to find the closest pair of points among the remaining points.
This problem has a time complexity of O(n*log(n)) for the best case and O(n^2) for the worst case, the space complexity is O(n)

Thankfully I have the solution with me-aswell:

import math

def closest_pair(points):
n = len(points)
if n <= 1:
return float('inf')

if n == 2:
return math.hypot(points[0][0] - points[1][0], points[0][1] - points[1][1])

mid = n // 2
left = points[:mid]
right = points[mid:]

dl = closest_pair(left)
dr = closest_pair(right)
d = min(dl, dr)

strip = [p for p in points if abs(p[0] - points[mid][0]) < d]
strip.sort(key=lambda p: p[1])

for i, p in enumerate(strip):
for j in range(i+1, min(i+7, len(strip))):
q = strip[j]
d = min(d, math.hypot(p[0] - q[0], p[1] - q[1]))

return d

Tip 1:To answer the question about static and dynamic binding, you should first define the terms and explain how they differ. Static binding refers to the process of linking a method call to the corresponding method definition at compile-time, while dynamic binding refers to the process of linking a method call to the corresponding method definition at runtime. You can give an example of each, such as an example of a static method in Java and an example of a virtual method in C++.
Tip 2:: Do practice for SQL queries. (JOIN specially)
Tip 3:have a good understanding of indexing in database systems, tree structures, and the advantages and disadvantages of different types of indexes.

Here is a possible solution for the news aggregator platform:


Scalability: To handle the high volume of data, the platform can be designed using a distributed architecture. The system can use a message queue to handle the incoming articles and distribute them to multiple worker nodes for processing. These worker nodes can process the articles in parallel, using NLP techniques to extract important information and summarize the news. The summary can then be stored in a distributed database, such as a NoSQL database like MongoDB or Cassandra, which can handle large amounts of data and provide high read and write performance.

Multi-Language support: To handle multiple languages, the platform can use language detection libraries to identify the language of the incoming articles. Once the language is detected, the appropriate NLP tools and models can be used to process the text. For example, if the article is in Spanish, the platform can use a Spanish language model for text summarization.

NLP: The platform can use NLP techniques such as text summarization, named entity recognition, and sentiment analysis to extract important information from the articles and provide a summary of the most important events. For example, the platform can use GPT-3 or BERT to extract the key phrases from the articles and use those to generate a summary.

Personalization: To provide a personalized summary of the news for each user, the platform can store user preferences in a database. When a user logs in, the platform can retrieve their preferences and use them to filter the articles and provide a summary of the most important events in their preferred topics.

User Interface: The platform can provide a web-based interface for users to browse and read the summarized news articles. The interface can be designed using a JavaScript framework, such as React or Angular, to provide a responsive and user-friendly experience. Users can search for articles by keywords, view the summary, and read the full article if they wish.

Tip 1: BE CONFIDENT
Tip 2: give real-life experience if possible ,otherwise try to formulate a realistic story