Passed 10 out of 12 test cases and genuinely have no idea what went wrong with the other two.
First, clarify the problem and edge cases, then discuss recursive and iterative approaches with their trade-offs. Choose the most efficient solution based on constraints, and analyze time and space complexity.
Pro tip: Mention how you would handle large trees to avoid stack overflow, showing awareness of production constraints. Also, relate the problem to real-world scenarios like file systems or organizational hierarchies to demonstrate practical thinking.
Ask clarifying questions to confirm the tree type, input format, and expected output. Identify edge cases such as empty tree, single node, skewed tree, and duplicate values.
Discuss both recursive (DFS) and iterative (BFS/stack) solutions. Compare their time and space complexities, and consider if the tree is a BST for optimized solutions.
Select the optimal approach based on constraints and explain your choice. Write clean code with meaningful variable names, handling edge cases explicitly.
Walk through the code with sample inputs, including edge cases. Verify correctness and complexity, and discuss potential optimizations or trade-offs.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Start by clarifying the problem statement and expected output, then outline your query logic step-by-step before writing SQL. Focus on correctness, efficiency, and handling edge cases, and explain your reasoning as you go.
Pro tip: Always discuss indexing and query performance implications, especially for large datasets typical at Flipkart. Mention how you would test the query with sample data to validate edge cases.
Ask questions to understand the exact problem, input tables, expected output, and any constraints (e.g., time range, duplicates).
Break down the problem into logical steps: identify necessary tables, joins, filters, aggregations, and window functions if needed.
Construct the SQL query incrementally, starting with FROM and JOINs, then WHERE, GROUP BY, HAVING, and finally SELECT with any window functions.
Review for performance (e.g., avoid SELECT *, use appropriate indexes) and mentally test with edge cases like NULLs, duplicates, or empty results.
Walk through the query, explain key decisions, and discuss potential alternatives or trade-offs.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Start by clarifying the problem constraints and edge cases, then discuss potential approaches and their trade-offs before coding. Implement the optimal solution in clean Python, explaining your reasoning as you go, and test with examples.
Pro tip: At Flipkart, interviewers value candidates who proactively discuss time and space complexity and consider scalability. Always mention how your solution would handle large inputs and potential optimizations.
Ask clarifying questions to fully grasp the problem requirements, constraints, and edge cases. Confirm input/output formats and any assumptions.
Brainstorm multiple solutions, from brute force to optimized, and analyze their time and space complexities. Choose the best approach based on constraints.
Write clean, modular Python code with meaningful variable names. Explain your logic as you code and handle edge cases.
Walk through your code with sample inputs, including edge cases, to verify correctness. If time permits, discuss potential optimizations or alternative implementations.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Only 6 out of 12 passed and this was supposedly the easiest one on the whole OA.
Start by restating the problem in your own words and clarifying constraints (input size, edge cases, expected complexity). Then propose the simplest correct solution, analyze its time/space complexity, and discuss potential optimizations or trade-offs. Finally, walk through a small example to validate the approach.
Pro tip: Even if the problem seems trivial, explicitly mention edge cases (empty input, single element, duplicates, overflow) and test your solution mentally. Interviewers at Flipkart value thoroughness and the ability to catch subtle bugs over speed.
Ask clarifying questions about input format, constraints, expected output, and edge cases. Confirm your understanding with the interviewer.
Outline a naive solution first, then explain how you can improve it. Mention time and space complexity for each.
Implement the chosen approach with meaningful variable names and modular structure. Handle edge cases explicitly.
Walk through a few test cases, including edge cases, to verify correctness. Dry-run the code step by step.
State the final complexity and discuss any further optimizations or trade-offs, even if not needed.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.