SDE - 1

Step 1: I initially approached the problem using a basic recursive solution, where I considered all possible steps (1, 2, or 3) at each position. However, this approach was inefficient due to overlapping subproblems and led to exponential time complexity.

Step 2: The interviewer suggested optimizing the solution, so I decided to implement a dynamic programming (DP) approach. I created an array to store the minimum steps required to reach each step, reducing redundant calculations.

Step 3: By applying the DP approach, I was able to calculate the minimum steps in O(N) time. The interviewer was pleased with the optimized solution and how I used dynamic programming to handle larger inputs efficiently.

Step 1: I initially approached the problem by iterating through each train's arrival and departure times and checking overlaps manually. This brute-force approach was inefficient and did not scale well with larger inputs.

Step 2: The interviewer suggested optimizing the solution. I decided to use a more efficient approach by sorting the arrival and departure times separately. This allows us to use a two-pointer technique to calculate the number of platforms needed.

Step 3: I implemented the following optimized approach:

Sort the arrival and departure arrays.
Use two pointers to traverse these sorted arrays: one pointer for arrival and one for departure.
Track the number of platforms required by comparing the current arrival and departure times. Increment the platform count for each arrival and decrement it for each departure.
Update the maximum number of platforms required during the traversal.
The optimized solution with sorting and the two-pointer technique ensured an efficient calculation of the minimum number of platforms required. The interviewer was satisfied with this approach due to its clarity and efficiency.

Tip 1: Define Clear Use Cases - Before diving into the design, clearly define the use cases and requirements for the app. Understanding what features are essential and how users will interact with the app will guide your design decisions.

Tip 2: Consider Scalability - Design your system to handle increasing loads efficiently. Use scalable data storage solutions and consider how your system will handle a growing number of users and transactions.

Tip 3: Focus on Data Consistency - Ensure that your system handles transactions and balances accurately. Implement mechanisms to prevent duplicate entries and inconsistencies in user balances, especially when handling concurrent operations.