18 posts tagged with "Interview Prep"

If you're heading into placement season or want to master one of the most versatile problem-solving techniques in DSA, this list is for you. Two Pointers and Sliding Window are patterns you'll encounter in almost every interview, whether it's a FAANG-style round or a product startup's online assessment.

These aren't random problems. They're hand-picked to cover every sub-pattern, from simple opposite-end pointers to complex variable-length window problems with character frequency maps.

I've organized them by pattern type because that's how your brain should work during interviews. Once you recognize "this needs a shrinking window" or "this is a classic two-sum variant," the rest follows naturally.

Connect with me on LinkedIn to stay updated with more coding resources, interview tips, and problem-solving strategies!

If you're preparing for placement season or looking to sharpen your Heap and Priority Queue skills, I've compiled a hand-picked list of problems that cover the depth and breadth of this topic.

This isn't a magic list that guarantees you'll ace every interview. But these are the standard problems and patterns I've consistently seen across interview experiences, company hiring tests, and coding assessments.

I've organized them by pattern, because that's how real interviews work. Once you recognize whether a problem needs a "Top K" approach, a "Two Heaps" setup, or a "K-Way Merge," the solution clicks into place.

Connect with me on LinkedIn to stay updated with more coding resources, interview tips, and problem-solving strategies!

If you're gearing up for placement season or trying to finally conquer DP (we've all been there!), I've compiled a list of hand-picked problems that cover the depth and breadth of dynamic programming.

Connect with me on LinkedIn to stay updated with more coding resources, interview tips, and problem-solving strategies!

This isn't a guaranteed ticket to ace every DP question. DP is hard, arguably the hardest topic in DSA interviews. But these are the standard problems and patterns that keep showing up in actual interviews, coding assessments, and company hiring tests.

I've organized these by pattern types because that's how your brain will work during interviews. You won't think "ah, this is LeetCode #123." You'll think "this looks like a path-counting problem" or "this feels like interval DP."

Not too many problems to overwhelm you. Not too few to leave gaps. Just the focused set you need to build that DP intuition.

Let's crack DP together!

If you're having your placement season in a few months or want to revise graph concepts, I've made a list of hand-picked problems to cover the depth and breadth of graphs.

This isn't a magic list that guarantees you'll crack every interview or assessment. But these are standard problems and patterns I've consistently seen across interview experiences, company blogs, and my own preparation journey.

I've organized these by pattern because that's how interviews work, they don't ask "solve graph problem #47." They ask problems that test whether you understand BFS, topological sort, or Union Find. Once you recognize the pattern, the solution follows.

Think of this as your focused revision toolkit. Not too overwhelming, not too sparse. just the right problems to build strong pattern recognition.

Let's gooo!

Connect with me on LinkedIn to stay updated with more coding resources, interview tips, and problem-solving strategies!

One of the most effective ways to prepare for online assessments is to practice the third and fourth questions from recent LeetCode contests, as these problems closely match the difficulty level and patterns commonly seen in actual OA rounds at top tech companies.

Connect with me on LinkedIn to stay updated with more coding resources, interview tips, and problem-solving strategies!

Below is a curated list of Q3 and Q4 problems from the most recent Weekly and Biweekly contests.

Hey everyone! Bit manipulation is one of the most powerful and elegant techniques in programming. I've spent years mastering bit tricks for both interviews and competitive programming, and I want to share a complete guide that will transform how you approach problems involving bits, bitwise operations, and binary representations.

The key insight: Bit manipulation isn't just about flipping bits, it's a problem-solving paradigm that enables incredibly efficient solutions to seemingly complex problems. Once you understand the fundamental bit tricks, you'll recognize optimization opportunities that others miss entirely.

Hey everyone! Dynamic Programming is often considered the hardest topic in DSA, but it doesn't have to be. I've spent months working through DP problems for both tech interviews and competitive programming, and I wanted to share a complete guide that demystifies this topic.

The key insight that changed everything for me, DP isn't one giant topic, it's actually 15-20 clear patterns. Once you recognize these patterns, most DP problems become straightforward. This guide includes curated problem lists, the best learning resources, and proven roadmaps for both interview prep and competitive programming.

Hey everyone! I've been working on graph problems for both tech interviews and competitive programming, and I wanted to share a comprehensive guide that covers both aspects. Many resources focus on just one side, but mastering graphs requires understanding both the interview patterns and the deeper algorithmic concepts used in CP.

This guide includes curated problem lists, the best learning resources I've found, and a clear roadmap for both paths.

Hey everyone! Greedy algorithms are one of the most elegant and intuitive problem-solving paradigms in computer science. I've spent years mastering greedy techniques for both interviews and competitive programming, and I want to share a complete guide that will transform how you approach optimization problems.

The key insight: Greedy algorithms are about making locally optimal choices that lead to globally optimal solutions. The challenge isn't implementation, it's recognizing when greedy works and proving correctness. Once you develop this intuition, you'll solve complex problems with surprisingly simple code.

Hey everyone! Strings are arguably the most frequently tested topic in technical interviews and competitive programming. I've spent years mastering string algorithms, and I want to share a complete roadmap that covers everything from basic manipulation to advanced pattern matching algorithms.

String problems aren't just about manipulating characters. They require understanding hashing, pattern matching, dynamic programming, sliding windows, two pointers, and even advanced algorithms like KMP, Z-algorithm, and suffix arrays. Master strings, and you'll have a massive advantage in any coding challenge.