Frequently Asked Questions

Quality beats quantity. Solving 100–150 problems with genuine understanding of the underlying patterns outperforms grinding 400+ problems superficially. Most interview questions are variations of ~15 core patterns. Once you can identify the pattern from the problem statement, solving unseen problems becomes straightforward.

• Two Sum — Hash Table / complement lookup
• Best Time to Buy and Sell Stock — Greedy one-pass
• Valid Parentheses — Stack
• Maximum Subarray — Kadane's algorithm
• Merge Intervals — Sorting + sweep
• Climbing Stairs — DP base case
• Number of Islands — BFS/DFS on grid
• Binary Search — Template for answer-space search

• 2–4 weeks: Basics (Array, String, Hash Table, Two Pointers)
• 4–6 weeks: Core algorithms (Binary Search, Trees, BFS/DFS)
• 6–10 weeks: Dynamic Programming + Advanced structures
• 10–12 weeks: Full readiness including system design awareness

The 30-day intensive plan on this site works for candidates who can dedicate 2–3 hours per day and already have programming experience.

Use the language you will be interviewed in. If you are applying for .NET developer roles at Microsoft, Infosys, Accenture, or product companies that use the .NET stack, practise in C#. Your solutions will look natural, you will know the idiomatic APIs, and you will not need to mentally translate from another language during the interview. Python is faster to write but irrelevant if the interview is conducted in C#.

Difficulty is relative and sometimes inconsistent on LeetCode, but as a rough guide:

• Easy: One data structure or straightforward loop. Expected solve time: 5–10 minutes. These appear as warm-up questions or phone screens at most companies.
• Medium: Requires combining 2–3 techniques. Expected solve time: 15–25 minutes. Most on-site interview questions are Medium difficulty.
• Hard: Complex DP, advanced graph algorithms, or non-obvious observations. Expected solve time: 30–45 minutes. Appear in later rounds at FAANG-level companies.

For most roles, focus 60% of your time on Mediums, 25% on Easys, and 15% on Hards.

Yes, for software engineering roles at most product and tech companies in 2024–2026. Microsoft, Amazon, Google, Meta, and thousands of startups use algorithmic coding rounds as part of their hiring process. Service companies (TCS, Wipro, Infosys, Cognizant) conduct their own aptitude+coding tests that overlap significantly with LeetCode Easy/Medium problems. Knowing the core patterns gives you a concrete edge.

Time complexity describes how the runtime of an algorithm scales with input size. Written as Big-O notation (O(n), O(n log n), O(n²), etc.), it lets interviewers and engineers compare algorithms without running them.

It matters in interviews for two reasons:

• Interviewers explicitly ask for it. You will not pass most on-site rounds without stating correct complexity.
• Problems have hidden time limits. A brute-force O(n²) solution may time out on 10⁵ inputs where an O(n log n) solution passes.

Every solution page on this site shows the Time and Space complexity as badges. Use them to build intuition.

LeetCode is the dominant platform for software engineering interview preparation globally and in India. C# is the natural language for .NET developers but is underrepresented in LeetCode solution repositories. GeeksforGeeks POTD (Problem of the Day) is the most popular daily coding challenge in India, and its community predominantly expects Java solutions. Maintaining both in a single site covers the two most common interview preparation workflows for Indian software developers.

A few checks:

1. Can you reduce time complexity by trading space? (e.g., use a hash map to avoid an inner loop)
2. Can you reduce space by computing on the fly instead of pre-storing? (e.g., rolling DP variables)
3. Is there a mathematical observation that eliminates the algorithm entirely? (common in Math-tagged problems)
4. Does your solution handle the worst-case input (all duplicates, sorted, reverse-sorted, single element)?

On LeetCode, click Discuss after submitting to see community solutions. Compare your Big-O with top-voted answers.

• PriorityQueue<TElement, TPriority> (.NET 6)
• Top-level statements and global usings
• Pattern matching with switch expressions
• Records and init-only properties
• BitOperations.PopCount(), Math.Log2()

The solutions on this site use modern C# and compile on LeetCode's current judge.