Hi👋SpeedAlgo • Deliberate Practice & Cognitive Ergonomics for Software Engineers

An interactive algorithm mastery and technical interview preparation platform published by Hi👋WebEnterprise. Built for senior and staff software engineers preparing for rigorous coding screens at top tech companies (FAANG/MAMAA).

13 Core Algorithmic Patterns & 225 Practice Problems

  • 1. Two Pointers (16 Paradigms, 43 Problems): Opposite ends, sorted pair sums, palindrome verification, trapping rain water, 3Sum, container with most water — includes the Sliding Window and Fast & Slow Pointers paradigms (contiguous subarray invariants, longest substrings, Floyd's cycle detection, linked list middle).
  • 2. Binary Search (9 Paradigms, 14 Problems): Monotonic predicate partitioning (feasible(x)), boundary search, rotated sorted arrays, square roots, minimum ship capacity, median of two sorted arrays, matrix median on value range.
  • 3. Bit Manipulation (5 Paradigms, 11 Problems): Counting set bits, XOR cancellation, bit reversal, bitmask pairing, maximum XOR with a bitwise trie.
  • 4. Math & Geometry (8 Paradigms, 14 Problems): Sieve of Eratosthenes, integer/roman conversions, modular arithmetic, geometric simulation.
  • 5. Tree/Graph Depth-First Search (15 Paradigms, 24 Problems): Path sums, lowest common ancestor, tree diameter, validating BSTs, tree DP (House Robber III, Binary Tree Cameras).
  • 6. Tree/Graph Breadth-First Search (5 Paradigms, 12 Problems): Level-order traversals, shortest path in unweighted graphs, zig-zag traversals, rotting oranges, word ladders.
  • 7. Graphs (12 Paradigms, 22 Problems): Topological sort, cycle detection, Dijkstra's algorithm, bipartite graph validation, network delay.
  • 8. Backtracking (6 Paradigms, 14 Problems): Subsets, permutations, combinations, constraint satisfaction, pruning, N-Queens, Sudoku solver.
  • 9. Dynamic Programming (13 Paradigms, 28 Problems): Memoization vs tabulation, 0/1 knapsack, unbounded knapsack, coin change, edit distance, longest common subsequence.
  • 10. Heap / Priority Queue (9 Paradigms, 11 Problems): Running medians, top-k elements, interval scheduling, IPO, k-way merges.
  • 11. Advanced Data Structures (7 Paradigms, 17 Problems): Trie (prefix tree), Union-Find (Disjoint Set Union), LRU Cache, LFU Cache, range-sum queries with updates.
  • 12. Stack (5 Paradigms, 9 Problems): Next greater element, largest rectangle in histogram, remove k digits, decode string, min stack.
  • 13. Intervals & Greedy (2 Paradigms, 6 Problems): Merge intervals, interval scheduling, meeting rooms by sweep line, jump game.

4-Stage Deliberate Practice Framework

  1. Stage 1 (Compare & Learn): Read the pattern's mental model, loop invariant and Big-O proof, compare the pattern's template with the problem's solution side by side, and use the step-by-step debugger. The solution can also be shown in C#, Java, TypeScript, C++, Go or Rust for almost every problem.
  2. Stage 2 (Active Recall): Rebuild the solution from memory in a code editor, with an invariant checklist and optional progressive hints, and check it against a judged test suite.
  3. Stage 3 (AI Interview Coach, coming soon): A mock-interview stage still in development; for now, students go straight from Stage 2 to Stage 4.
  4. Stage 4 (Solve on Your Own): Solve a new problem on your own against a 15-minute timer; your code is graded against a test suite. Python and TypeScript run in your browser and C# runs on our server (design problems grade in Python and TypeScript).

Equipped with a spaced-repetition review hub on a fixed 7-step schedule (1 day up to 90 days), a two-pane Studio workspace, and study notes.

Pricing, Access & Commercial Terms

  • Core Curriculum: 100% Free. No credit card required.
  • Coins: New accounts get 40 free coins once, the daily claim adds +20 coins once a day, and inviting a friend earns you +25 coins when they complete their first practice step. These are the only ways to earn coins.
  • AI Coach: Each AI coach question costs 1-5 coins, priced by the server according to its size.
  • BYOK (Bring Your Own Key): AI coaching is free with your own Google Gemini, OpenAI or OpenRouter API key (BYOK).
  • Extras: Coins also unlock extras for 24 hours: a Recall hint level (1 coin), a Solve solution reveal (2), a LeetCode problem card's solutions (1) and a pattern's extra canonical problems (1).
  • Payments & Refunds: Nothing on the site is sold for money: coins can only be earned, never bought. There are no subscriptions or charges, so there is nothing to refund.
  • Platform Operator: Hi👋WebEnterprise. Support & policies at hispeedalgo.com.
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Hi👋SpeedAlgo

Invariant-First Algorithmic Mastery

Arena
238Items
Theory Context•Two Pointers & Sliding Window
MediumLC 19

Remove Nth Node From End of List (LeetCode 19)

Target Frequency:MetaGoogleAmazon

Your input is a linked list's head plus an integer n. Delete the node that sits n positions from the end of the list, then return the (possibly new) head.

Follow up: Can you find and delete that node in one pass, without first counting the list's length?

Worked Examples

Example 1
Input:head = [1,2,3,4,5], n = 2
Output:[1,2,3,5]
12345
Explanation: The 2nd node from the end is 4. Removing it yields 1 -> 2 -> 3 -> 5.
Example 2
Input:head = [1], n = 1
Output:[]
Explanation: The only node in the list is removed, leaving an empty list.
Example 3
Input:head = [1,2], n = 1
Output:[1]
Explanation: The 1st node from the end (the tail node 2) is removed, leaving [1].

⚖️Formal Constraints & Bounds

  • The number of nodes in the list is sz.

  • 1 <= sz <= 30

  • 0 <= Node.val <= 100

  • 1 <= n <= sz

Deep-Dive & Conceptual Insights

Core Insight

A dummy node plus a lead pointer that starts n nodes ahead of the trail pointer puts the trail pointer on the node before the target, even when the target is the head.

Real-World Scenario & Production Applications

LRU cache tail invalidation, packet queue tail trimming, and undo-history fixed-depth truncation.

Step-by-Step Execution Trace Table

Phaselead postrail posAction
Dummy InitDummyDummydummy = ListNode(0, head), then lead and trail both start on dummy
Open The GapNode 2 (moved n = 2 steps)DummyOnly lead moves, so it is n nodes ahead of trail
Move TogetherNode 5 (last node)Node 3Both move one node per step, so the gap stays n; the loop stops when lead.next is empty
UnlinkNode 5Node 3trail.next = trail.next.next (Node 4 is removed)
Code Shape
Archetype Code Shape
Python
1dummy = ListNode(0, head)
2lead = trail = dummy
3for _ in range(n):
4 lead = lead.next
5while lead.next:
6 lead = lead.next
7 trail = trail.next
8trail.next = trail.next.next
9return dummy.next

Conceptual Narrative

🧭 Conceptual Foundation & Pattern Intuition

You can't count backward from the end of a singly linked list — there's no way to peek at length - n. So this trick never counts from the end at all.

🚶🚶 The Analogy: Walking a Fixed-Length Rope Between Two Hikers

Imagine two hikers connected by a rope that is exactly n steps long. Both start at the same place, on the dummy node. The lead hiker walks n steps alone, which pulls the rope tight. From then on, both hikers walk forward together, one step at a time, and the gap stays n steps. The lead hiker stops on the last node of the trail. The trailing hiker is then n steps behind, which is the node just before the one you need to remove.

🔑 The Key Idea in the Code

The dummy node at the very start exists purely so "the node before the head" is a real, addressable node too — letting the exact same gap-walk logic remove the head itself without a special case.

  • Deleting head node without a dummy sentinel: If n == len(list), removing the nth node from the end removes head. Without a dummy.next = head sentinel, you lose the list reference.

  • Pairing the gap with the wrong loop test: trail must stop on the node immediately PRECEDING the target. With while lead.next: the gap is n; with while lead: the gap would have to be n + 1. Mixing them removes the wrong node.

  • Memory leak by not severing deleted node: In languages with manual memory management (C++/C#), forgetting to free or detach the deleted node causes a memory leak.

Senior SWE Reasoning Architecture

4-Phase Thought Process Model

Pattern Recognition Signals

The 10-second spot

Single-pass deletion relative to linked list tail.

Formulating the Predicate & Invariants

Turning intuition into a boolean rule

Invariant: lead is exactly n nodes ahead of trail during the whole walk.

Silent Failure Traps & Edge Cases

Where confident candidates still lose points

  • Deleting the head node: always use a dummy node pointing to head to prevent null pointer exceptions.

The 60-Second Interview Pitch

Say this out loud before you type a single line

"I create a dummy node before head and start lead and trail on it. I move lead n nodes ahead, then I move lead and trail together until lead.next is empty. The gap stays n, so trail is now on the node before the target, and I set trail.next = trail.next.next. I return dummy.next. It runs in O(N) time and O(1) space."

Big-O Invariant Derivation

Complexity & Mathematical Proof

TIME COMPLEXITY

O(L)

Look at the execution steps: lead moves n nodes ahead of trail, then both pointers move one node per step until lead.next is empty. lead visits each node at most once, so the walk is one pass of at most L steps. trail is then on the node before the target.

SPACE COMPLEXITY

O(1) Auxiliary

Look at memory allocations: the code is iterative, so the call stack stays constant. It stores one dummy node and the two references lead and trail, which is O(1) space.

Formal Recurrence Relation

T(L) = L + 1 node steps = O(L)

Derivation Progression

Gap Creation

n initial hops

Moves lead n nodes from the dummy node while trail stays on it.

Synchronous Advance

L - n synchronous hops

Both pointers advance together until lead.next is empty.

Constant-Time Splicing

trail.next = trail.next.next

Node is unlinked in O(1) pointer updates.

Variable Definitions

LLL

Total number of nodes in the linked list

nnn

Position of the node to remove, counted from the end of the list (1 is the last node)

Memory Architecture & Bounds

🟣 Call Stack

O(1) Iterative

🔵 Auxiliary Heap

O(1) Dummy node and 2 pointers

🟢 Output Space

O(1) Head reference

Boundary Best / Worst Cases

Best Case

O(L)O(L)O(L)

Average Case

O(L)O(L)O(L)

Worst Case

O(L)O(L)O(L)

Pointer Invariant Transition Progression

Pointer Invariant Transition Progression
Synthesizing vector architecture diagram...
Staff+ Engineering Perspective

Senior SWE Deconstruction & Hardware Caveats

ARCHITECTURAL SIGNALS & INTERVIEW TRIGGERS

Triggers: "remove n-th node from end of list", "do this in one pass". Fixed-distance lead pointer pattern.

CONSTRAINTS & BOUNDS

N≤30,n≤lengthN \le 30, n \le \text{length}N≤30,n≤length. Single-pass O(L)O(L)O(L) time and O(1)O(1)O(1) memory.

FAANG PRODUCTION TRAPS & EDGE CASES

Removing the head node (when n=lengthn =\text{length}n=length). The sentinel dummy node absorbs head deletion uniformly without special branching.

Theory Context•Two Pointers & Sliding Window
MediumLC 19

Remove Nth Node From End of List (LeetCode 19)

Target Frequency:MetaGoogleAmazon

Your input is a linked list's head plus an integer n. Delete the node that sits n positions from the end of the list, then return the (possibly new) head.

Follow up: Can you find and delete that node in one pass, without first counting the list's length?

Worked Examples

Example 1
Input:head = [1,2,3,4,5], n = 2
Output:[1,2,3,5]
12345
Explanation: The 2nd node from the end is 4. Removing it yields 1 -> 2 -> 3 -> 5.
Example 2
Input:head = [1], n = 1
Output:[]
Explanation: The only node in the list is removed, leaving an empty list.
Example 3
Input:head = [1,2], n = 1
Output:[1]
Explanation: The 1st node from the end (the tail node 2) is removed, leaving [1].

⚖️Formal Constraints & Bounds

  • The number of nodes in the list is sz.

  • 1 <= sz <= 30

  • 0 <= Node.val <= 100

  • 1 <= n <= sz

Deep-Dive & Conceptual Insights

Core Insight

A dummy node plus a lead pointer that starts n nodes ahead of the trail pointer puts the trail pointer on the node before the target, even when the target is the head.

Real-World Scenario & Production Applications

LRU cache tail invalidation, packet queue tail trimming, and undo-history fixed-depth truncation.

Step-by-Step Execution Trace Table

Phaselead postrail posAction
Dummy InitDummyDummydummy = ListNode(0, head), then lead and trail both start on dummy
Open The GapNode 2 (moved n = 2 steps)DummyOnly lead moves, so it is n nodes ahead of trail
Move TogetherNode 5 (last node)Node 3Both move one node per step, so the gap stays n; the loop stops when lead.next is empty
UnlinkNode 5Node 3trail.next = trail.next.next (Node 4 is removed)
Code Shape
Archetype Code Shape
Python
1dummy = ListNode(0, head)
2lead = trail = dummy
3for _ in range(n):
4 lead = lead.next
5while lead.next:
6 lead = lead.next
7 trail = trail.next
8trail.next = trail.next.next
9return dummy.next

Conceptual Narrative

🧭 Conceptual Foundation & Pattern Intuition

You can't count backward from the end of a singly linked list — there's no way to peek at length - n. So this trick never counts from the end at all.

🚶🚶 The Analogy: Walking a Fixed-Length Rope Between Two Hikers

Imagine two hikers connected by a rope that is exactly n steps long. Both start at the same place, on the dummy node. The lead hiker walks n steps alone, which pulls the rope tight. From then on, both hikers walk forward together, one step at a time, and the gap stays n steps. The lead hiker stops on the last node of the trail. The trailing hiker is then n steps behind, which is the node just before the one you need to remove.

🔑 The Key Idea in the Code

The dummy node at the very start exists purely so "the node before the head" is a real, addressable node too — letting the exact same gap-walk logic remove the head itself without a special case.

  • Deleting head node without a dummy sentinel: If n == len(list), removing the nth node from the end removes head. Without a dummy.next = head sentinel, you lose the list reference.

  • Pairing the gap with the wrong loop test: trail must stop on the node immediately PRECEDING the target. With while lead.next: the gap is n; with while lead: the gap would have to be n + 1. Mixing them removes the wrong node.

  • Memory leak by not severing deleted node: In languages with manual memory management (C++/C#), forgetting to free or detach the deleted node causes a memory leak.

Senior SWE Reasoning Architecture

4-Phase Thought Process Model

Pattern Recognition Signals

The 10-second spot

Single-pass deletion relative to linked list tail.

Formulating the Predicate & Invariants

Turning intuition into a boolean rule

Invariant: lead is exactly n nodes ahead of trail during the whole walk.

Silent Failure Traps & Edge Cases

Where confident candidates still lose points

  • Deleting the head node: always use a dummy node pointing to head to prevent null pointer exceptions.

The 60-Second Interview Pitch

Say this out loud before you type a single line

"I create a dummy node before head and start lead and trail on it. I move lead n nodes ahead, then I move lead and trail together until lead.next is empty. The gap stays n, so trail is now on the node before the target, and I set trail.next = trail.next.next. I return dummy.next. It runs in O(N) time and O(1) space."

Big-O Invariant Derivation

Complexity & Mathematical Proof

TIME COMPLEXITY

O(L)

Look at the execution steps: lead moves n nodes ahead of trail, then both pointers move one node per step until lead.next is empty. lead visits each node at most once, so the walk is one pass of at most L steps. trail is then on the node before the target.

SPACE COMPLEXITY

O(1) Auxiliary

Look at memory allocations: the code is iterative, so the call stack stays constant. It stores one dummy node and the two references lead and trail, which is O(1) space.

Formal Recurrence Relation

T(L) = L + 1 node steps = O(L)

Derivation Progression

Gap Creation

n initial hops

Moves lead n nodes from the dummy node while trail stays on it.

Synchronous Advance

L - n synchronous hops

Both pointers advance together until lead.next is empty.

Constant-Time Splicing

trail.next = trail.next.next

Node is unlinked in O(1) pointer updates.

Variable Definitions

LLL

Total number of nodes in the linked list

nnn

Position of the node to remove, counted from the end of the list (1 is the last node)

Memory Architecture & Bounds

🟣 Call Stack

O(1) Iterative

🔵 Auxiliary Heap

O(1) Dummy node and 2 pointers

🟢 Output Space

O(1) Head reference

Boundary Best / Worst Cases

Best Case

O(L)O(L)O(L)

Average Case

O(L)O(L)O(L)

Worst Case

O(L)O(L)O(L)

Pointer Invariant Transition Progression

Pointer Invariant Transition Progression
Synthesizing vector architecture diagram...
Staff+ Engineering Perspective

Senior SWE Deconstruction & Hardware Caveats

ARCHITECTURAL SIGNALS & INTERVIEW TRIGGERS

Triggers: "remove n-th node from end of list", "do this in one pass". Fixed-distance lead pointer pattern.

CONSTRAINTS & BOUNDS

N≤30,n≤lengthN \le 30, n \le \text{length}N≤30,n≤length. Single-pass O(L)O(L)O(L) time and O(1)O(1)O(1) memory.

FAANG PRODUCTION TRAPS & EDGE CASES

Removing the head node (when n=lengthn =\text{length}n=length). The sentinel dummy node absorbs head deletion uniformly without special branching.

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