DEV Community: Shaan Yadav

Rectangle Overlap | LEETCODE 836 | Solve In Seconds | Amazon Most Asked Interview |

Shaan Yadav — Mon, 14 Sep 2026 03:22:34 +0000

Rectangle Overlap | LEETCODE 836 | Solve In Seconds | Amazon Most Asked Interview |

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Rectangle Overlap LeetCode 836 cracked with best visualization in just three lines — Amazon Adobe Meta Docusign interview favorite with O(1) width and height logic made instantly clear.

LeetCode Question: https://leetcode.com/problems/rectangle-overlap/
Solution (Java / Python / C++ / C): https://github.com/Shaanworkspace/YOUTUBE-DRIVE/blob/main/Leetcode_Daily/LC_836_Rectangle_Overlap_All_Languages.md

Rectangle Overlap LeetCode 836 gives you two rectangles as rec1 equals x1 y1 x2 y2 and rec2 equals x1 y1 x2 y2. Each rectangle uses only two diagonal points — bottom-left x1 y1 and top-right x2 y2. Draw lines through those points and you get all four sides. The task is whether the common overlapping area is strictly greater than zero. Edge or corner touching returns false, separate rectangles return false, only positive width and positive height together return true. This video makes that definition fully visual, then solves it in O(1) time and O(1) space with the common width and height projection trick asked at Amazon, Adobe, Meta Facebook and Docusign.

Every part of the video is mapped to chapters. We define rectangles, decode the array input, visualize the three cases, plot a full example, derive common width as min of right edges minus max of left edges, derive common height the same way on Y, show why multiplying to area fails when both are negative, and fix it by checking width greater than zero and height greater than zero directly. The three-line Java code is typed, run on samples and submitted to pass all tests. Code in Java, Python, C++ and C is linked above.

00:00 — Why Visualizing Rectangle Overlap Makes It Easy
Three lines become obvious once you see rectangles as projections — a picture beats memorizing formulas.

01:00 — How Two Points Define Any Rectangle
x1 y1 bottom-left and x2 y2 top-right — four lines through them build the full rectangle and explain rec1 rec2 input.

02:15 — True Overlap Needs Positive Common Area
Overlap needs strictly positive common area — touching at an edge with zero area returns false.

03:05 — Overlap Versus Touching Versus Separate Cases
Case one positive area, case two shares only boundary, case three completely separate — see all three side by side.

04:50 — Grid Example Walkthrough Step By Step
Plot rec1 0 0 to 4 4 and rec2 2 2 to 6 5 on one grid and shade the intersecting rectangle.

06:15 — Finding Common Width With Min Max Formula
Common width equals min of x2 minus max of x1 — project both intervals on X and take the overlap length.

07:50 — Finding Common Height Same Trick On Y Axis
Common height equals min of y2 minus max of y1 — same min-max logic on Y gives vertical overlap.

09:15 — Why Area Multiplication Fails With Negatives
Both negative into positive fakes an area — see the counterexample that breaks naive area greater than zero check.

10:30 — Fix With Width And Height Greater Than Zero
Return width greater than zero and height greater than zero — no multiplication, handles edge-touching correctly.

11:20 — Three Line Code Submit And Pass All Tests
Type three lines in Java, run samples, submit to pass all tests and grab Python C++ C from GitHub link above.

FAQ

Q1: How is a rectangle given in Rectangle Overlap LeetCode 836?
A1: As four integers x1 y1 x2 y2 where x1 y1 is bottom-left and x2 y2 is top-right. Two arrays rec1 and rec2 define the two rectangles to test.

Q2: When do two rectangles actually overlap?
A2: Only when both common width and common height are strictly greater than zero. Width is min of x2 minus max of x1, height is min of y2 minus max of y1. Edge touching returns false.

Q3: Why not just check if area greater than zero?
A3: When rectangles are on opposite sides both width and height are negative and their product becomes positive, faking a valid area. Checking width and height separately avoids that trap.

Q4: What is the time and space complexity?
A4: O(1) time and O(1) space — two mins, two maxes, two subtractions and two comparisons with no loops or extra structures.

Q5: Which companies ask Rectangle Overlap in interviews?
A5: Amazon, Adobe, Meta Facebook and Docusign. It looks easy but tests whether you handle projection overlap and edge cases correctly.

Q6: Does touching at an edge count as overlap?
A6: No. The overlapping area must be greater than zero, so sharing only a boundary line or a single point is not overlap and must return false.

Q7: Where can I get the code in all four languages?
A7: Java, Python, C++ and C are pushed to GitHub at the Solution link above. Use it to compare syntax and submit in your preferred language.

LeetCode #LeetCode836 #RectangleOverlap #CodingInterview #DSA #Algorithms #AmazonInterview #ShaanLabs

📺 Watch the full walkthrough on YouTube:

Watch the full Rectangle Overlap | LEETCODE 836 | Solve In Seconds | Amazon Most Asked Interview | walkthrough on YouTube

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Image Overlap | LEETCODE 835 | Solve In Seconds | Google Microsoft Most Asked Interview

Shaan Yadav — Sun, 13 Sep 2026 05:53:36 +0000

Image Overlap | LEETCODE 835 | Solve In Seconds | Google Microsoft Most Asked Interview

🧠 Want the intuition, not just the code? Join 2,000+ coders getting daily LeetCode breakdowns (Telegram gets them first):

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Image Overlap is a matrix shifting problem asked at Google and Microsoft interviews — master the best brute force visualization approach to count maximum overlapping ones in seconds with full clarity.

LeetCode Question: https://leetcode.com/problems/image-overlap/
Solution (Java / Python / C++ / C): https://github.com/Shaanworkspace/YOUTUBE-DRIVE/blob/main/Leetcode_Daily/LC_835_Image_Overlap_All_Languages.md
LeetCode 835 Image Overlap asks you to find the maximum number of overlapping ones when one matrix is shifted over another. The brute force approach tries every possible horizontal and vertical shift, counting overlaps at each position — O(n^4) time, O(1) space. This video gives you the best visual explanation of how matrix shifting works, why translation is the key concept, and walks through the complete code with examples. Asked at Google and Microsoft interviews.

00:00 — Best Visualization of How Matrix Shifting Works
This question can be made easy with visualization. I will visualize the problem and solution for you so you understand how things move inside a matrix.

00:36 — Matrix Shifting: How One Grid Moves Over Another
Let us start with the problem. Image overlap means shifting one matrix over another and counting where both have a 1 at the same position.

01:07 — Translation Explained: Why Shifting Is the Key
Translation is the core concept. When you shift img1 by some amount, each cell maps to a new position. We need to find the shift that gives maximum overlap.

02:09 — Visualizing All Possible Shifts Step by Step
A matrix of size n can shift up, down, left, or right. Each shift position is a unique translation. We try every possible shift and count overlapping ones.

04:47 — Counting Overlaps at Each Shift Position
For each shift, iterate through all cells. If img1 has a 1 and the shifted position in img2 also has a 1, increment the count. Track the maximum across all shifts.

07:05 — Example Walkthrough: Counting Overlaps Live
Let us see a concrete example. Walk through the matrix shift by shift, showing exactly which cells overlap and how the count changes at each position.

09:38 — Brute Force Code: Four Nested Loops Explained
The solution uses four nested loops: two for the shift range and two for the matrix cells. For each shift, count overlapping ones. Return the maximum count found.

12:01 — Submit and Verify: All Test Cases Pass
Let us hit submit and see. The brute force approach passes all test cases within the time limit.

13:33 — Complexity Analysis and Subscribe
O(n^4) time, O(1) space. Every shift position checked, every cell compared. Feel free to subscribe and share with friends who need this.

FAQ

Q1: What is LeetCode 835 Image Overlap about?
A1: Given two binary matrices img1 and img2, return the maximum number of ones that overlap when img1 is shifted (translated) in any direction over img2.

Q2: What is the brute force approach for Image Overlap?
A2: Try every possible horizontal and vertical shift of img1 over img2. For each shift, count how many positions have a 1 in both matrices. Return the maximum count.

Q3: What is the time complexity of the brute force solution?
A3: O(n^4) — two loops for the shift range (each up to 2n-1 positions) and two loops for the matrix cells (n x n). For each of the O(n^2) shifts, we check O(n^2) cells.

Q4: Can this problem be solved faster than O(n^4)?
A4: Yes. Using FFT (Fast Fourier Transform) you can solve it in O(n^2 log n) time, but the brute force O(n^4) is simpler and passes within constraints for n up to 30.

Q5: Why is this problem asked at Google and Microsoft?
A5: It tests matrix manipulation, nested loop logic, and the ability to think about shifting/translation — core skills for image processing and grid-based problems.

Q6: What is the space complexity of the brute force approach?
A6: O(1) — no extra data structures needed. We only use a few integer variables for counting and tracking the maximum overlap.

LeetCode #LeetCode835 #ImageOverlap #DSA #Algorithms #Matrix #CodingInterview #ShaanLabs

📺 Watch the full walkthrough on YouTube:

Watch the full Image Overlap | LEETCODE 835 | Solve In Seconds | Google Microsoft Most Asked Interview walkthrough on YouTube

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[Boost]

Shaan Yadav — Thu, 10 Sep 2026 05:16:21 +0000

Shaan Yadav

Sep 10

Count Nodes Equal to Average of Subtree | LEETCODE 2265 | Solve In Seconds

#productivity #ai #webdev #programming

2 min read

Count Nodes Equal to Average of Subtree | LEETCODE 2265 | Solve In Seconds

Shaan Yadav — Thu, 10 Sep 2026 05:15:51 +0000

This video breaks down LeetCode 2265 — Count Nodes Equal to Average of Subtree — a medium binary tree problem where post-order DFS returns (sum, count) pairs to check the average condition at every node in linear time.

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Count Nodes Equal to Average of Subtree is a medium binary tree problem asked in real interviews — DFS traversal computing subtree sum and count, checking the average condition at every node.

LeetCode Question: https://leetcode.com/problems/count-nodes-equal-to-average-of-subtree/ Solution (Java / Python / C++ / C): https://github.com/Shaanworkspace/YOUTUBE-DRIVE/blob/main/Leetcode_Daily/LC_2265_Count_Nodes_Equal_to_Average_of_Subtree_All_Languages.md

Why this approach beats the others
Post-order DFS returns (sum, count) — no competitor explains the two-value return pattern this clearly. We teach why children must be processed before parents.
O(n) vs O(n²) explained — brute force recalculates subtrees repeatedly. The optimal approach visits each node exactly once. We show both approaches side by side.
The average condition — node value equals floor(sum / count). We walk through exactly when this condition triggers and why integer division matters.
Pattern recognition — this same post-order aggregate pattern solves Maximum Average Subtree, Diameter of Binary Tree, and Binary Tree Maximum Path Sum.
Four-language code (Java/Python/C++/C) — no competitor provides all four with the same clean logic.
How to solve Count Nodes Equal to Average of Subtree (Step by Step)
Define a DFS helper that returns a pair: (subtree sum, subtree count).
Base case: null node returns (0, 0).
At each node, recursively get left and right pairs.
Compute sum = node.val + left.sum + right.sum, count = 1 + left.count + right.count.
If sum / count == node.val, increment the answer.
Return (sum, count) to the parent.
Notes for US interview prep
Title, description, tags, chapters = American English spelling.
Upload accurate English .srt captions (do NOT rely on auto-captions).
Schedule in EST window: Tue/Wed 2-4 PM EST (1:30 AM IST next day) via YouTube Schedule.
Long-form hashtags trimmed to 3 (LeetCode2265, CountNodesAverageSubtree, BinaryTreeDFS).
Create playlists: “LeetCode Daily”, “LeetCode Medium”, “Binary Tree DFS Patterns”.
Channel About section + keywords = US terms (LeetCode, coding interview, binary tree, DFS).
📺 Watch the full walkthrough on YouTube: https://youtu.be/cvpBMPbbRQc?si=9UmrodgirbT7IdqT

Watch the full Count Nodes Equal to Average of Subtree | LEETCODE 2265 | Solve In Seconds walkthrough on YouTube

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Construct Uniform Parity Array II | LEETCODE 3876 | Solve In Seconds |

Shaan Yadav — Thu, 03 Sep 2026 17:10:22 +0000

Construct Uniform Parity Array II | LEETCODE 3876 | Solve In Seconds |

This video breaks down Leetcode 3876 — Construct Uniform Parity Array II — the harder Part 2 where the positive-difference constraint creates a bottleneck at the minimum odd number. We explain why the smallest odd number determines the answer: if any even number is smaller than it, you cannot make everything odd. The solution runs in O(n) time with O(1) space. We connect this to Part 1 (3875) and teach the parity math that separates medium from easy problems.

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Construct Uniform Parity Array II is the harder Part 2 of Leetcode 3876 where the minimum odd number bottleneck determines whether you can build a uniform parity array — and here is exactly how it works.

LeetCode Question: https://leetcode.com/problems/construct-uniform-parity-array-ii/
Solution (Java / Python / C++ / C): https://github.com/Shaanworkspace/YOUTUBE-DRIVE/blob/main/Leetcode_Daily/LC_3876_Construct_Uniform_Parity_Array_II_All_Languages.md

Why this approach beats the others

Minimum-odd bottleneck explanation — no competitor explains WHY the smallest odd number is the bottleneck. We teach the deep insight.
Part 1 connection — we position this as the continuation from 3875, driving views to both videos.
"WHY BEHIND EVERYTHING ?" hook — we explain the reasoning, not just the code. This is what interviews test.
Clean SEO title with "Solve In Seconds" — no competitor has this hook for 3876.
Four-language code (Java/Python/C++/C) — no competitor provides all four.

Notes for US interview prep

Title, description, tags, chapters = American English spelling.
Upload accurate English .srt captions (do NOT rely on auto-captions). cam.srt has word-level timestamps — clean into proper .srt format.
Schedule in EST window: Tue/Wed 2-4 PM EST (1:30 AM IST next day) via YouTube Schedule.
Long-form hashtags trimmed to 3 (Leetcode3876, ConstructUniformParityArray, ParityArray).
Create playlists: "LeetCode Daily", "LeetCode Medium", "Brain Teasers LeetCode".
Channel About section + keywords = US terms (LeetCode, coding interview, parity array, brain teaser).

📺 Watch the full walkthrough on YouTube:

Watch the full Construct Uniform Parity Array II | LEETCODE 3876 | Solve In Seconds | walkthrough on YouTube

🚀 Cracking Amazon / Google interviews? Get every new LeetCode solution the moment it drops. Join 2,000+ coders who never miss a walkthrough:

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Construct Uniform Parity Array I | LEETCODE 3875 | Solve In Seconds |

Shaan Yadav — Wed, 02 Sep 2026 05:20:25 +0000

Construct Uniform Parity Array I | LEETCODE 3875 | Solve In Seconds |

This video breaks down Leetcode 3875 — Construct Uniform Parity Array I — a brain teaser where the entire solution is two words: return true. We explain the parity math behind WHY it always works: if all elements share the same parity, copy them; if mixed, subtract odd from even to make everything odd. Every case returns true. The video teaches you to think before coding, which is the real skill interviews test. We also connect this to Part 2, which adds real construction constraints.

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Construct Uniform Parity Array I is a brain teaser Leetcode 3875 problem where the solution is just two words — return true — and here is exactly why that works every single time.

LeetCode Question: https://leetcode.com/problems/construct-uniform-parity-array-i/
Solution (Java / Python / C++ / C): https://github.com/Shaanworkspace/YOUTUBE-DRIVE/blob/main/Leetcode_Daily/LC_3875_Construct_Uniform_Parity_Array_I_All_Languages.md

Why this approach beats the others

"2 Word Solution Only" hook — no competitor leads with the brain teaser angle. This drives massive curiosity clicks.
Parity MATH explanation — we explain WHY it always returns true, not just THAT it returns true. Competitors just say "return true" without the why.
Part 2 connection — we position this as the foundation for the harder problem, giving viewers a reason to watch both.
"Think Before You Code" lesson — we teach the meta-skill of analyzing before coding, which is what interviews actually test.
Clean SEO title with "Solve In Seconds" — no competitor has this hook for 3875.

Notes for US interview prep

Title, description, tags, chapters = American English spelling.
Upload accurate English .srt captions (do NOT rely on auto-captions). The current cam.srt is a word-level transcript — clean it into proper .srt format with correct timing before upload.
Schedule in EST window: Tue/Wed 2-4 PM EST (1:30 AM IST next day) via YouTube Schedule.
Long-form hashtags trimmed to 3 (Leetcode3875, ConstructUniformParityArray, BrainTeaser).
Create playlists: "LeetCode Daily", "LeetCode Easy", "Brain Teasers LeetCode".
Channel About section + keywords = US terms (LeetCode, coding interview, brain teaser).

📺 Watch the full walkthrough on YouTube:

Watch the full Construct Uniform Parity Array I | LEETCODE 3875 | Solve In Seconds | walkthrough on YouTube

🚀 Cracking Amazon / Google interviews? Get every new LeetCode solution the moment it drops. Join 2,000+ coders who never miss a walkthrough:

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Minimum Moves to Clean the Classroom | LEETCODE 3568 | Solve In Seconds | Bloomberg Interview

Shaan Yadav — Tue, 01 Sep 2026 06:47:05 +0000

Minimum Moves to Clean the Classroom | LEETCODE 3568 | Solve In Seconds | Bloomberg Interview

This video walks through LeetCode 3568: Minimum Moves to Clean the Classroom, a Bloomberg interview problem. We explain the BFS + Bitmask DP approach for grid traversal with energy constraints and litter collection. The solution tracks state as (row, col, energy, mask) and uses BFS to find the minimum moves. Reset areas restore energy, obstacles block movement, and the bitmask tracks which litter cells have been collected. Full Java code walkthrough included.

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Minimum Moves to Clean the Classroom LeetCode 3568 solution — the cleanest BFS and Bitmask DP walkthrough for grid traversal with energy constraints and litter collection. This Bloomberg interview problem tests your ability to manage state in a grid while collecting all litter items before energy runs out.

LeetCode Question: https://leetcode.com/problems/minimum-moves-to-clean-the-classroom/
Solution (Java / Python / C++ / C): https://github.com/Shaanworkspace/YOUTUBE-DRIVE/blob/main/Leetcode_Daily/LC_3568_Minimum_Moves_to_Clean_the_Classroom_All_Languages.md

Why this approach beats the others

Bloomberg branding (verified asking company) — most competitors do not mention the company.
"Solve In Seconds" hook — fast-paced, no fluff, no classroom-style rambling.
BFS + Bitmask DP explained with visual state transitions — not just code dumps.
Energy management + R cell strategy clearly explained — the trickiest part most videos skip.
Professional thumbnail with stored photo, LeetCode logo, Bloomberg logo, and "INTERVIEW APPROACH" text.

Notes for US interview prep

Schedule for US peak: Tuesday or Wednesday 2:00 PM EST (12:30 AM IST next day) via YouTube Schedule.
Upload accurate English .srt captions (not auto-generated) for clean indexing.
Long-form hashtags trimmed to 1-2 (per 2026 data: 17% fewer views with hashtags on long-form).
Company playlists: "Bloomberg LeetCode Interview", "Amazon LeetCode", "Google LeetCode".
Community engagement: r/leetcode, Blind, LinkedIn, Dev.to.

📺 Watch the full walkthrough on YouTube:

Watch the full Minimum Moves to Clean the Classroom | LEETCODE 3568 | Solve In Seconds | Bloomberg Interview walkthrough on YouTube

🚀 Cracking Amazon / Google interviews? Get every new LeetCode solution the moment it drops. Join 2,000+ coders who never miss a walkthrough:

📢 Telegram: https://t.me/opentech_shaanlabs
💬 WhatsApp: https://chat.whatsapp.com/CvlyO3ZBBoTBiPLDXpEJME?mode=gi_t

Min Max Nodes Between Critical Points | LEETCODE 2058 | Solve In Seconds | Amazon Interview |

Shaan Yadav — Mon, 31 Aug 2026 06:00:26 +0000

Min Max Nodes Between Critical Points | LEETCODE 2058 | Solve In Seconds | Amazon Interview |

This video covers LeetCode 2058 — Find the Minimum and Maximum Number of Nodes Between Critical Points. A medium-difficulty linked list problem asked at Amazon, Google, Meta, and Microsoft. The solution uses a three-node sliding window (previous, current, next) to detect local maxima and local minima in a single O(n) pass. The optimal O(1) space approach tracks only four variables: firstCriticalIndex, previousCriticalIndex, minDistance, and currentIndex. An alternative ArrayList approach stores all critical indices and scans for min/max distance. Edge cases covered: fewer than two critical points returns [-1, -1], strictly increasing/decreasing lists, and tied values.

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Find the Minimum and Maximum Number of Nodes Between Critical Points is a medium linked list problem asked at Amazon, Google, Meta, and Microsoft — the easiest two-pointer explanation with both O(1) and O(n) space solutions explained in seconds.

LeetCode Question: https://leetcode.com/problems/find-the-minimum-and-maximum-number-of-nodes-between-critical-points/
Solution (Java / Python / C++ / C): https://github.com/Shaanworkspace/YOUTUBE-DRIVE/blob/main/Leetcode_Daily/LC_2058_Find_the_Minimum_and_Maximum_Number_of_Nodes_Between_Critical_Points_All_Languages.md

Why this approach beats the others

Company angle: "Amazon Most Asked Interview" — no competitor owns this for LC 2058.
Two approaches: O(1) space optimal + ArrayList walkthrough — competitors show only one.
"Solve In Seconds" promise — unique hook for this specific problem.
O(n) to O(1) Space Complexity text on thumbnail — the exact upgrade interviewers want to see.
FAANG company logos on thumbnail (Amazon, Google, Meta, Microsoft) — instant credibility.
Long-tail keyword coverage: "three-node window", "local maximum minimum linked list", "critical points O(1) space" — competitors miss these.

Notes for US interview prep

Schedule in EST window: Tue/Wed 2-4 PM EST or Sun 10 AM EST
Upload accurate English .srt captions (cam.srt grounded)
Company playlists: Amazon LeetCode, Google LeetCode, Meta LeetCode, Microsoft LeetCode
Long-form hashtags trimmed to 3-5
English metadata (American spelling: behavior, optimize, color)

📺 Watch the full walkthrough on YouTube:

Watch the full Min Max Nodes Between Critical Points | LEETCODE 2058 | Solve In Seconds | Amazon Interview | walkthrough on YouTube

🚀 Cracking Amazon / Google interviews? Get every new LeetCode solution the moment it drops. Join 2,000+ coders who never miss a walkthrough:

📢 Telegram: https://t.me/opentech_shaanlabs
💬 WhatsApp: https://chat.whatsapp.com/CvlyO3ZBBoTBiPLDXpEJME?mode=gi_t

Removing Minimum and Maximum From Array | LEETCODE 2091 | Solve In Seconds | Amazon Most Asked

Shaan Yadav — Mon, 31 Aug 2026 05:22:11 +0000

Removing Minimum and Maximum From Array | LEETCODE 2091 | Solve In Seconds | Amazon Most Asked

This video covers LeetCode 2091 — Removing Minimum and Maximum From Array. A medium-difficulty greedy array problem asked at Amazon, Google, Meta, and Microsoft. The solution finds the indices of the minimum and maximum elements in a single O(n) pass, then compares three deletion strategies: delete from front only, delete from back only, or delete one from each end (the "pincer" move). The answer is the minimum of all three. Optimal O(1) space using only four variables. Edge cases covered: single element (return 1), adjacent min/max at one end (return 2), min/max at opposite ends (return 2).

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Removing Minimum and Maximum From Array (LeetCode 2091) — the easiest greedy explanation with a clean O(n) walkthrough and full Java, Python, C++ and C code.

LeetCode Question: https://leetcode.com/problems/removing-minimum-and-maximum-from-array/
Solution (Java / Python / C++ / C): https://github.com/Shaanworkspace/YOUTUBE-DRIVE/blob/main/Leetcode_Daily/LC_2091_Removing_Minimum_and_Maximum_From_Array_All_Languages.md

Why this approach beats the others

Company angle: "Amazon Most Asked Interview" — no competitor owns this for LC 2091.
Three strategies compared: front-only, back-only, pincer — competitors show only one.
"Solve In Seconds" promise — unique hook for this specific problem.
"3 STRATEGIES | O(n) TIME" text on thumbnail — the exact upgrade interviewers want to see.
FAANG company logos on thumbnail (Amazon, Google, Meta, Microsoft) — instant credibility.
Long-tail keyword coverage: "greedy array", "three deletion strategies", "front back removal" — competitors miss these.

Notes for US interview prep

Schedule in EST window: Tue/Wed 2-4 PM EST or Sun 10 AM EST
Upload accurate English .srt captions (cam.srt grounded)
Company playlists: Amazon LeetCode, Google LeetCode, Meta LeetCode, Microsoft LeetCode
Long-form hashtags trimmed to 3-5
English metadata (American spelling: behavior, optimize, color)

📺 Watch the full walkthrough on YouTube:

Watch the full Removing Minimum and Maximum From Array | LEETCODE 2091 | Solve In Seconds | Amazon Most Asked walkthrough on YouTube

🚀 Cracking Amazon / Google interviews? Get every new LeetCode solution the moment it drops. Join 2,000+ coders who never miss a walkthrough:

📢 Telegram: https://t.me/opentech_shaanlabs
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Removing Minimum and Maximum From Array | LEETCODE 2091 | Solve In Seconds | Amazon Most Asked

Shaan Yadav — Sun, 30 Aug 2026 03:23:46 +0000

Removing Minimum and Maximum From Array | LEETCODE 2091 | Solve In Seconds | Amazon Most Asked

This video solves LeetCode 2091 Removing Minimum and Maximum From Array with a greedy O(n) approach. It finds the min and max indices in one pass, then compares three deletion patterns — front only, back only, and both ends — returning the minimum count. The walkthrough covers the worked example, edge cases (n=1, adjacent indices, extremes at the ends), complexity O(n)/O(1), and the full Java, Python, C++ and C code, framed for Amazon, Google and Meta interviews.

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Removing Minimum and Maximum From Array is a LeetCode medium problem — the easiest greedy O(n) way to delete both extremes with the fewest front-or-back removals, explained with a clear visual walkthrough.

Why this approach beats the others

Exact primary keyword "Removing Minimum and Maximum From Array" leads the title and the description snippet, while blogs/video competitors bury it.
O(n) greedy explained visually (three deletion cases) beats the common O(n log n) sorting explanations.
Black cinematic, face-forward thumbnail with LeetCode + Amazon/Google logos and two distinct taglines ("CRACK INTERVIEW", "JUST WATCH IT") out-clicks plain-code thumbnails.
Full Java/Python/C++/C code in one GitHub file covers every language searchers type.
Chapters, 6 FAQ, and US-EST scheduling maximize YouTube + Google + AI-search indexing.

Notes for US interview prep

Metadata in American English spelling (behavior, color, optimize, favorite).
Upload accurate English .srt captions (the recording cam.srt) — do NOT rely on auto-captions; this unlocks Google video carousels and AI-search citations.
Schedule publish Tue/Wed 2-4 PM EST (Sun 10 AM EST also strong) via YouTube Schedule; 3 PM EST = 1:30 AM IST next day.
Build playlists: "Amazon LeetCode Interview", "Google LeetCode", "Meta LeetCode" for session autoplay.
Long-form hashtags kept to 3 (trim spam); push Shorts clipping the Solve-in-Seconds hook (vertical 9:16, captions) Fri 4-7 PM EST.
Confirm US% rising in YouTube Studio -> Audience -> Geography.

📺 Watch the full walkthrough on YouTube:

Watch the full Removing Minimum and Maximum From Array | LEETCODE 2091 | Solve In Seconds | Amazon Most Asked walkthrough on YouTube

🧠 Want the intuition, not just the code? Join 2,000+ coders getting daily LeetCode breakdowns (Telegram gets them first):

📢 Telegram: https://t.me/opentech_shaanlabs
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Make Lexicographically Smallest Array by Swapping Elements | LEETCODE 2948 | Solve In Seconds |

Shaan Yadav — Sat, 29 Aug 2026 04:43:26 +0000

Make Lexicographically Smallest Array by Swapping Elements | LEETCODE 2948 | Solve In Seconds |

LeetCode 2948 — Make Lexicographically Smallest Array by Swapping Elements. You may swap two elements only if their value gap is ≤ limit, so values form limit-groups (connected components). Sort value-index pairs, group by the limit, then place each group's smallest values at its smallest original indices. Result: lexicographically smallest array in O(n log n) time, O(n) space. Asked at Amazon, Google, Atlassian, Uber, IBM, PhonePe.

🧠 Want the intuition, not just the code? Join 2,000+ coders getting daily LeetCode breakdowns (Telegram gets them first):

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Make Lexicographically Smallest Array by Swapping Elements (LeetCode 2948) — the easiest limit-group swap explanation with a clean O(n log n) walkthrough and full Java, Python, C++ and C code.

LeetCode Question: https://leetcode.com/problems/make-lexicographically-smallest-array-by-swapping-elements/
Solution (Java / Python / C++ / C): https://github.com/Shaanworkspace/YOUTUBE-DRIVE/blob/main/Leetcode_Daily/LC_2948_Make_Lexicographically_Smallest_Array_by_Swapping_Elements_All_Languages.md

Why this approach beats the others

Exact long-tail title + "Solve In Seconds" + company interview angle competitors lack.
All four languages (Java/Python/C++/C) in ONE GitHub file — rivals show one language.
Face-forward black cinematic thumbnail with LeetCode + Amazon logos and two distinct taglines ("CRACK INTERVIEW", "JUST WATCH IT") for max CTR.
Chapter-level keyword extraction + FAQ + clean transcript feed YouTube, Google and AI search (GEO) citations.

Notes for US interview prep

Metadata in American English spelling (behavior, color, optimize, favorite) — applied in title/description/tags.
Captions: upload the accurate English .srt already recorded at /Users/shaanyadav/MyStorage/youtube/Recoding/cam.srt to YouTube (do NOT rely on auto-captions; fixes technical terms like "lexicographically").
Schedule in EST: long-form Tue/Wed 2-4 PM EST (publish 1-2h before). IST = EST + 10h30m, so 3 PM EST = 1:30 AM IST next day — use YouTube Schedule.
Playlists: create "Amazon LeetCode Interview", "Google LeetCode", "LeetCode Daily" and add this video.
Long-form hashtags trimmed to 2 (#LeetCode #AmazonInterview) per 2026 data (hashtags can cut long-form views).
AI/GEO: chapters act as citable H2 chunks; clean transcript + direct-answer description help ChatGPT/Gemini/Perplexity cite the video.

📺 Watch the full walkthrough on YouTube:

Watch the full Make Lexicographically Smallest Array by Swapping Elements | LEETCODE 2948 | Solve In Seconds | walkthrough on YouTube

🧠 Want the intuition, not just the code? Join 2,000+ coders getting daily LeetCode breakdowns (Telegram gets them first):

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Lexicographically Smallest Palindromic Permutation Greater Than Target | LEETCODE 3734 | Solve In Seconds

Shaan Yadav — Fri, 28 Aug 2026 04:17:31 +0000

Lexicographically Smallest Palindromic Permutation Greater Than Target | LEETCODE 3734 | Solve In Seconds

The video opens with the LeetCode 3734 problem statement and two examples, then explains frequency counting and the at-most-one-odd rule. It builds the left half with greedy choices constrained by the target prefix and backtracking, mirrors it into the final palindrome, and proves the O(26*n) time / O(26) space complexity. The flash texts "YOU WILL DO IT", "HARD MADE EASIEST" and "JUST WATCH IT" reinforce confidence.

🧠 Want the intuition, not just the code? Join 2,000+ coders getting daily LeetCode breakdowns (Telegram gets them first):

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Lexicographically Smallest Palindromic Permutation Greater Than Target (LeetCode 3734, Hard) is explained the easiest way — a clear greedy plus backtracking walkthrough that builds the smallest palindrome permutation strictly greater than the target.

LeetCode Question: https://leetcode.com/problems/lexicographically-smallest-palindromic-permutation-greater-than-target/
Solution (Java / Python / C++ / C): https://github.com/Shaanworkspace/YOUTUBE-DRIVE/blob/main/Leetcode_Daily/LC_3734_Lexicographically_Smallest_Palindromic_Permutation_Greater_Than_Target_All_Languages.md

Why this approach beats the others

Exact long-tail keyword in title, description opening, FAQ, chapters, tags and hashtags — future "optimized" videos cannot outrank.
Real GitHub code (4 languages) with a permanent blob link — competitors only paste screenshots.
21-section depth: chapters, FAQ, US SEO, scheduling, AI/GEO-ready transcript structure.
Cinematic black thumbnail with LeetCode logo + flash texts and a real bearded face — highest CTR.

Notes for US interview prep

Metadata in American English (behavior/color/optimize).
Upload accurate English .srt captions (NOT auto) so YouTube + Google + AI engines index the palindrome permutation logic.
Schedule long-form Tue/Wed 2-4 PM EST (Shorts Fri 4-7 PM EST) via YouTube Schedule.
Build playlists: Amazon LeetCode Interview, Google LeetCode, Meta LeetCode, Microsoft LeetCode (even though no company is verified for 3734, these catch sibling searches).
Long-form hashtags trimmed to 3 (US RPM focus).

📺 Watch the full walkthrough on YouTube:

Watch the full Lexicographically Smallest Palindromic Permutation Greater Than Target | LEETCODE 3734 | Solve In Seconds walkthrough on YouTube

🧠 Want the intuition, not just the code? Join 2,000+ coders getting daily LeetCode breakdowns (Telegram gets them first):

📢 Telegram: https://t.me/opentech_shaanlabs
💬 WhatsApp: https://chat.whatsapp.com/CvlyO3ZBBoTBiPLDXpEJME?mode=gi_t