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).

12 Core Algorithmic Patterns & 168 Practice Problems

  • 1. Two Pointers (9 Paradigms, 32 Problems): Converging pointers, sorted pair sums, container with most water, trapping rain water, 3Sum, plus the Sliding Window and Fast & Slow Pointers paradigms (Floyd cycle detection, monotonic window invariants, longest substrings, minimum window).
  • 2. Binary Search (8 Paradigms, 12 Problems): Monotonic predicate partitioning, boundary searching, rotated arrays, median of two sorted arrays, matrix median on value range.
  • 3. Bit Manipulation (5 Paradigms, 8 Problems): Bitmasking, XOR tricks, counting set bits, subset enumeration via bitmasks.
  • 4. Math & Geometry (5 Paradigms, 10 Problems): Sieve of Eratosthenes, integer/roman conversions, modular arithmetic, geometric simulation.
  • 5. Tree/Graph Depth-First Search (8 Paradigms, 17 Problems): Path sums, lowest common ancestor, tree diameter, subtree serialization, validating BSTs.
  • 6. Tree/Graph Breadth-First Search (4 Paradigms, 11 Problems): Level-order traversals, shortest path, rotting oranges, word ladders.
  • 7. Graphs (6 Paradigms, 14 Problems): Topological sort, cycle detection, Dijkstra, bipartite validation, network delay.
  • 8. Backtracking (5 Paradigms, 13 Problems): Subsets, permutations, combinations, constraint satisfaction, pruning, N-Queens.
  • 9. Dynamic Programming (7 Paradigms, 14 Problems): Memoization vs tabulation, knapsack, coin change, edit distance, longest common subsequence.
  • 10. Heap / Priority Queue (8 Paradigms, 10 Problems): Running medians, top-k elements, interval scheduling, IPO, k-way merges.
  • 11. Advanced Data Structures (5 Paradigms, 13 Problems): Trie, Union-Find, LRU Cache, LFU Cache, Monotonic Stacks.
  • 12. Intervals & Stack / Miscellaneous (7 Paradigms, 14 Problems): Merge intervals, daily temperatures, largest rectangle in histogram, trapping rain water via stack.

4-Stage Deliberate Practice Framework

  1. Stage 1 (Compare & Learn): Multi-language Rosetta Stone contrasting abstract invariants with concrete solutions across Python, C#, Java, TypeScript, C++, Go, and Rust.
  2. Stage 2 (Active Recall): Reconstruct algorithmic template invariants from memory with real-time feedback before looking at solutions.
  3. Stage 3 (Senior SWE AI Mock Coach): Simulated senior mock interview evaluating Big-O space/time tradeoffs, edge cases, and code reviews in Monaco Editor.
  4. Stage 4 (Solve on Your Own): Timed sandbox challenges verified against automated test suites in Python, C#, Java, and TypeScript.

Equipped with SM-2 Spaced Repetition Review Hub, Studio Cockpit workspace layout, and interactive study notes.

Pricing, Access & Commercial Terms

  • Core Curriculum: 100% Free. No credit card required.
  • Compute Coins: 40 free coins upon signup, +20 daily login bonus, +25 referral bonus.
  • 24-Hour AI Coaching Pass: 5 compute coins unlocks unlimited senior SWE AI coaching for a full 24 hours.
  • BYOK (Bring Your Own Key): Completely free unlimited AI coaching if using your own Gemini/OpenAI API key.
  • Refund & Subscription Policy: No recurring charges, no subscription traps, and no paid paywalls. Free tier provides full learning path.
  • Platform Operator: Hi👋WebEnterprise Inc. Support & policies at hispeedalgo.com.
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Hi👋SpeedAlgo

Invariant-First Algorithmic Mastery

180Items
Theory Context•Two Pointers & Sliding Window
EasyLC 203

Remove Linked List Elements (LeetCode 203)

Branchless Head Mutation via a Synthetic Predecessor

Target Frequency:AmazonMetaAppleMicrosoft

Given a singly linked list, execute structural modifications (such as deleting target nodes, merging multiple lists, partitioning by value, or reversing sub-segments) where the head node itself may be modified or removed, in O(n)O(n)O(n) time with zero branching edge cases.

The Technique Invariant: Instead of cluttering list algorithms with special-case logic for empty lists (head == null) or head deletions (if curr == head), prepend a synthetic Sentinel (Dummy) Node: dummy = ListNode(0, head).

  • The sentinel node guarantees that every valid list node—including the original head—possesses a non-null predecessor pointer (prev.next = curr.next).
  • Edge cases of deleting the first element, inserting before the head, or operating on single-element lists become identical to internal node operations.
  • Return dummy.next as the sanitized, unambiguous head of the modified list.

Worked Examples

Example 1
Input:head = [1,2,6,3,4,5,6], val = 6
Output:[1,2,3,4,5]
1263456
Explanation: Both nodes holding value 6 are removed, including one in the interior and one at the tail.
Example 2
Input:head = [], val = 1
Output:[]
Explanation: The list is empty, so there is nothing to remove.
Example 3
Input:head = [7,7,7,7], val = 7
Output:[]
7777
Explanation: Every node -- including the original head -- matches val and is removed, leaving an empty list.

⚖️Formal Constraints & Bounds

  • The number of nodes in the list is in the range [0, 10^4]

  • 1 <= Node.val <= 50

  • 0 <= val <= 50

Deep-Dive & Conceptual Insights

Why It Works & Core Invariant

\forall nodes v ∈ List, ; predecessor(v) e null — the dummy node guarantees uniform node deletion and insertion semantics.

Real-World Scenario & Production Applications

Java's LinkedList/LinkedHashMap and Redis's list implementations keep permanent sentinel head/tail nodes so insertion, removal, and LRU eviction never special-case the boundary elements; the Linux kernel's intrusive struct list_head anchors circular doubly-linked lists the same way to avoid null-pointer checks inside interrupt handlers.

Core Invariant Specification & Code Shape
Archetype Code Shape
Python
1Prepend a dummy node before head: dummy = ListNode(0, head)
2Initialize prev = dummy, curr = head
3If curr.val == val: prev.next = curr.next; else advance prev = curr
4Advance curr = curr.next every iteration and return dummy.next

Target: Remove Linked List Elements (LeetCode 203). Creates a synthetic predecessor for the real head, so the very first node no longer needs special-case handling when it is removed.

Boundary Model: Permanent Boundary Guard Interval [DummyHead, DummyTail]

Initialize dummy_head.next = head (or dummy_head.next = dummy_tail for doubly-linked). All operations return dummy_head.next.

Loop Invariant Termination

dummy = ListNode(0); dummy.next = head; prev = dummy; while curr: ...; return dummy.next

Conceptual Narrative

The Flash of Genius: Deleting or replacing a linked list's head node forces every mutation to branch on if curr == head, since the head has no predecessor to redirect. Prepending a synthetic dummy node before the real head (dummy = ListNode(0, head)) gives every node -- including the original head -- a valid predecessor. Every removal collapses to the single uniform line prev.next = curr.next, and the sanitized result is always dummy.next.

The Mental Model Analogy: The Physical Bookends on a Crowded Shelf

Imagine organizing books on an open-ended shelf. If there are no bookends, whenever you want to insert a new book at the very left edge, you have to be extremely careful that the book does not tumble off the shelf onto the floor! You need a special rule for the first book, a special rule for the last book, and a general rule for books in the middle. But if you screw two heavy steel bookends permanently into the wood at position 0 and position 100—bookends that are never removed—now EVERY book, even the very first and very last, is always nestled comfortably between two existing objects! You no longer need special edge cases for 'inserting at head' or 'deleting at tail'. One single, universal rule handles 100% of cases without a single dropped book.

  • Pitfall: Deleting the head node normally needs a special case because it has no predecessor to redirect -- what gives it one?

  • Pitfall: Once prev starts at the dummy node, prev.next = curr.next works identically no matter which node is removed.

  • Pitfall: The final answer is never head directly -- it's always dummy.next, since the true head may have been removed.

Senior SWE Reasoning Architecture

4-Phase Thought Process Model

Senior SWE thought process architecture for Sentinel (Dummy Head) Node Injection.

Pattern Recognition Signals

The 10-second spot

The operation modifies a linked list, and the head node might be removed, swapped, or prepended. Instantiate a dummy sentinel node.

Formulating the Predicate & Invariants

Turning intuition into a boolean rule

Initialize prev = dummy and curr = head. Now every node, including index 0, has a valid prev pointer.

Silent Failure Traps & Edge Cases

Where confident candidates still lose points

  • Invariant: dummy_head.next is the most recent; dummy_tail.prev is the least recent.

  • Zero branches: Adding and removing nodes never checks for None.

The 60-Second Interview Pitch

Say this out loud before you type a single line

Verify on empty lists head = None and singleton lists [1]. Both execute cleanly through the general loop without crashing.

Deleting or replacing a linked list's head node forces every mutation to branch on if curr == head, since the head has no predecessor to redirect. Prepending a synthetic dummy node before the real head (dummy = ListNode(0, head)) gives every node -- including the original head -- a valid predecessor. Every removal collapses to the single uniform line prev.next = curr.next, and the sanitized result is always dummy.next.

Big-O Invariant Derivation

Complexity & Mathematical Proof

TIME COMPLEXITY

O(n)

Allocating a sentinel dummy node takes O(1) time. By eliminating conditional branch checks (if head is None, if curr.next is None) inside the traversal loop, the instruction count per iteration decreases. Total traversal time is strictly O(N) with fewer total CPU instructions.

SPACE COMPLEXITY

O(1)

Exactly one dummy node (or two in doubly-linked structures) is allocated on the heap or stack. Auxiliary space complexity is strictly O(1).

Formal Recurrence Relation

lim⁡k→∞N2k=1  ⟹  2k=N  ⟹  k=log⁡2N\lim_{k \to \infty} \frac{N}{2^k} = 1 \implies 2^k = N \implies k = \log_2 Nlimk→∞​2kN​=1⟹2k=N⟹k=log2​N

Allocating a sentinel dummy node takes O(1) time. By eliminating conditional branch checks (if head is None, if curr.next is None) inside the traversal loop, the instruction count per iteration decreases. Total traversal time is strictly O(N) with fewer total CPU instructions.

Pointer Invariant Transition Progression

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

Senior SWE Deconstruction & Hardware Caveats

ARCHITECTURAL SIGNALS & INTERVIEW TRIGGERS

Instantiates dummy = ListNode(0, head) without being prompted by the interviewer. • Returns dummy.next rather than attempting to track a mutable head reference. • Designs LRU Cache with two sentinel nodes (head and tail) to achieve branchless O(1)O(1)O(1) node splicing. • Explains CPU branch predictor benefits of removing boundary condition checks.

CONSTRAINTS & BOUNDS

The number of nodes in the list is in the range [0, 10^4]. 1 <= Node.val <= 50. 0 <= val <= 50

FAANG PRODUCTION TRAPS & EDGE CASES

In the Linux kernel linked list implementation (<linux/list.h>), all circular doubly-linked lists use a sentinel struct list_head anchor to avoid null pointer dereferencing in kernel interrupt handlers.

Core Algorithmic State Invariants

1. Monotonic Window Expansion

The right pointer advances forward, absorbing the incoming element into the running aggregation state (frequency map, sum, or set).

2. Window Validity & Contraction Invariant

When window constraints are violated (or while valid when seeking minimal length), the left pointer increments to evict elements and restore the required invariant.

3. Amortized Linear Termination

Because each element enters and exits the window at most once, total operations across both pointers are bounded by 2N, guaranteeing strictly linear O(N) execution.

Theory Context•Two Pointers & Sliding Window
EasyLC 203

Remove Linked List Elements (LeetCode 203)

Branchless Head Mutation via a Synthetic Predecessor

Target Frequency:AmazonMetaAppleMicrosoft

Given a singly linked list, execute structural modifications (such as deleting target nodes, merging multiple lists, partitioning by value, or reversing sub-segments) where the head node itself may be modified or removed, in O(n)O(n)O(n) time with zero branching edge cases.

The Technique Invariant: Instead of cluttering list algorithms with special-case logic for empty lists (head == null) or head deletions (if curr == head), prepend a synthetic Sentinel (Dummy) Node: dummy = ListNode(0, head).

  • The sentinel node guarantees that every valid list node—including the original head—possesses a non-null predecessor pointer (prev.next = curr.next).
  • Edge cases of deleting the first element, inserting before the head, or operating on single-element lists become identical to internal node operations.
  • Return dummy.next as the sanitized, unambiguous head of the modified list.

Worked Examples

Example 1
Input:head = [1,2,6,3,4,5,6], val = 6
Output:[1,2,3,4,5]
1263456
Explanation: Both nodes holding value 6 are removed, including one in the interior and one at the tail.
Example 2
Input:head = [], val = 1
Output:[]
Explanation: The list is empty, so there is nothing to remove.
Example 3
Input:head = [7,7,7,7], val = 7
Output:[]
7777
Explanation: Every node -- including the original head -- matches val and is removed, leaving an empty list.

⚖️Formal Constraints & Bounds

  • The number of nodes in the list is in the range [0, 10^4]

  • 1 <= Node.val <= 50

  • 0 <= val <= 50

Deep-Dive & Conceptual Insights

Why It Works & Core Invariant

\forall nodes v ∈ List, ; predecessor(v) e null — the dummy node guarantees uniform node deletion and insertion semantics.

Real-World Scenario & Production Applications

Java's LinkedList/LinkedHashMap and Redis's list implementations keep permanent sentinel head/tail nodes so insertion, removal, and LRU eviction never special-case the boundary elements; the Linux kernel's intrusive struct list_head anchors circular doubly-linked lists the same way to avoid null-pointer checks inside interrupt handlers.

Core Invariant Specification & Code Shape
Archetype Code Shape
Python
1Prepend a dummy node before head: dummy = ListNode(0, head)
2Initialize prev = dummy, curr = head
3If curr.val == val: prev.next = curr.next; else advance prev = curr
4Advance curr = curr.next every iteration and return dummy.next

Target: Remove Linked List Elements (LeetCode 203). Creates a synthetic predecessor for the real head, so the very first node no longer needs special-case handling when it is removed.

Boundary Model: Permanent Boundary Guard Interval [DummyHead, DummyTail]

Initialize dummy_head.next = head (or dummy_head.next = dummy_tail for doubly-linked). All operations return dummy_head.next.

Loop Invariant Termination

dummy = ListNode(0); dummy.next = head; prev = dummy; while curr: ...; return dummy.next

Conceptual Narrative

The Flash of Genius: Deleting or replacing a linked list's head node forces every mutation to branch on if curr == head, since the head has no predecessor to redirect. Prepending a synthetic dummy node before the real head (dummy = ListNode(0, head)) gives every node -- including the original head -- a valid predecessor. Every removal collapses to the single uniform line prev.next = curr.next, and the sanitized result is always dummy.next.

The Mental Model Analogy: The Physical Bookends on a Crowded Shelf

Imagine organizing books on an open-ended shelf. If there are no bookends, whenever you want to insert a new book at the very left edge, you have to be extremely careful that the book does not tumble off the shelf onto the floor! You need a special rule for the first book, a special rule for the last book, and a general rule for books in the middle. But if you screw two heavy steel bookends permanently into the wood at position 0 and position 100—bookends that are never removed—now EVERY book, even the very first and very last, is always nestled comfortably between two existing objects! You no longer need special edge cases for 'inserting at head' or 'deleting at tail'. One single, universal rule handles 100% of cases without a single dropped book.

  • Pitfall: Deleting the head node normally needs a special case because it has no predecessor to redirect -- what gives it one?

  • Pitfall: Once prev starts at the dummy node, prev.next = curr.next works identically no matter which node is removed.

  • Pitfall: The final answer is never head directly -- it's always dummy.next, since the true head may have been removed.

Senior SWE Reasoning Architecture

4-Phase Thought Process Model

Senior SWE thought process architecture for Sentinel (Dummy Head) Node Injection.

Pattern Recognition Signals

The 10-second spot

The operation modifies a linked list, and the head node might be removed, swapped, or prepended. Instantiate a dummy sentinel node.

Formulating the Predicate & Invariants

Turning intuition into a boolean rule

Initialize prev = dummy and curr = head. Now every node, including index 0, has a valid prev pointer.

Silent Failure Traps & Edge Cases

Where confident candidates still lose points

  • Invariant: dummy_head.next is the most recent; dummy_tail.prev is the least recent.

  • Zero branches: Adding and removing nodes never checks for None.

The 60-Second Interview Pitch

Say this out loud before you type a single line

Verify on empty lists head = None and singleton lists [1]. Both execute cleanly through the general loop without crashing.

Deleting or replacing a linked list's head node forces every mutation to branch on if curr == head, since the head has no predecessor to redirect. Prepending a synthetic dummy node before the real head (dummy = ListNode(0, head)) gives every node -- including the original head -- a valid predecessor. Every removal collapses to the single uniform line prev.next = curr.next, and the sanitized result is always dummy.next.

Big-O Invariant Derivation

Complexity & Mathematical Proof

TIME COMPLEXITY

O(n)

Allocating a sentinel dummy node takes O(1) time. By eliminating conditional branch checks (if head is None, if curr.next is None) inside the traversal loop, the instruction count per iteration decreases. Total traversal time is strictly O(N) with fewer total CPU instructions.

SPACE COMPLEXITY

O(1)

Exactly one dummy node (or two in doubly-linked structures) is allocated on the heap or stack. Auxiliary space complexity is strictly O(1).

Formal Recurrence Relation

lim⁡k→∞N2k=1  ⟹  2k=N  ⟹  k=log⁡2N\lim_{k \to \infty} \frac{N}{2^k} = 1 \implies 2^k = N \implies k = \log_2 Nlimk→∞​2kN​=1⟹2k=N⟹k=log2​N

Allocating a sentinel dummy node takes O(1) time. By eliminating conditional branch checks (if head is None, if curr.next is None) inside the traversal loop, the instruction count per iteration decreases. Total traversal time is strictly O(N) with fewer total CPU instructions.

Pointer Invariant Transition Progression

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

Senior SWE Deconstruction & Hardware Caveats

ARCHITECTURAL SIGNALS & INTERVIEW TRIGGERS

Instantiates dummy = ListNode(0, head) without being prompted by the interviewer. • Returns dummy.next rather than attempting to track a mutable head reference. • Designs LRU Cache with two sentinel nodes (head and tail) to achieve branchless O(1)O(1)O(1) node splicing. • Explains CPU branch predictor benefits of removing boundary condition checks.

CONSTRAINTS & BOUNDS

The number of nodes in the list is in the range [0, 10^4]. 1 <= Node.val <= 50. 0 <= val <= 50

FAANG PRODUCTION TRAPS & EDGE CASES

In the Linux kernel linked list implementation (<linux/list.h>), all circular doubly-linked lists use a sentinel struct list_head anchor to avoid null pointer dereferencing in kernel interrupt handlers.

Core Algorithmic State Invariants

1. Monotonic Window Expansion

The right pointer advances forward, absorbing the incoming element into the running aggregation state (frequency map, sum, or set).

2. Window Validity & Contraction Invariant

When window constraints are violated (or while valid when seeking minimal length), the left pointer increments to evict elements and restore the required invariant.

3. Amortized Linear Termination

Because each element enters and exits the window at most once, total operations across both pointers are bounded by 2N, guaranteeing strictly linear O(N) execution.

Rosetta Dual-Monaco Comparison
Python 3
CANONICAL INVARIANT TEMPLATE
Loading...
CONCRETE: REMOVE LINKED LIST ELEMENTS (LEETCODE 203)
T = O(n)S = O(1)
Loading...
Pattern Implementation Mapping TableCanonical Invariant ⟷ Concrete Code ⟷ Engineering Rationale
Canonical InvariantConcrete CodeEngineering Rationale
dummy = ListNode(0, head)dummy = ListNode(0, head)Creates a synthetic predecessor for the real head, so the very first node no longer needs special-case handling when it is removed.
prev, curr = dummy, headprev, curr = dummy, headAnchors prev at the sentinel so the loop invariant prev.next == curr holds even on the first iteration.
if should_remove(curr, target): prev.next = curr.nextif curr.val == val: prev.next = curr.nextRemoves the current node with the exact same line whether it is the original head, an interior node, or the tail -- zero branching on position.
return dummy.nextreturn dummy.nextReturns the sanitized head. If the original head itself was removed, dummy.next already points at its replacement automatically.
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