Recover a BST with Two Swapped Nodes

What you’ll build / What this tests

This premium javascript coding focuses on Recover a BST with Two Swapped Nodes. You’ll apply tree and bst thinking with intermediate level constraints. The prompt emphasizes Two nodes in a Binary Search Tree were swapped by mistake. Implement recoverBST(root) to fix the….

Learning goals

• Translate the prompt into a clear javascript API signature and return shape.
• Apply tree, bst, algorithms techniques to implement recover a bst with two swapped nodes.
• Handle intermediate edge cases without sacrificing readability.
• Reason about time/space complexity and trade-offs in javascript.

Key decisions to discuss

• Define the exact input/output contract before coding.
• Choose iteration vs higher-order methods for readability.
• Prioritize predictable edge-case handling over micro-optimizations.

Evaluation rubric

• Correctness: covers required behaviors and edge cases.
• Clarity: readable structure and predictable control flow.
• Complexity: avoids unnecessary work for large inputs.
• API discipline: no mutation of inputs; returns expected shape.
• Testability: solution is easy to unit test.

Constraints / Requirements

• Preserve input order and handle empty arrays safely.
• Use a stable cache key and avoid collisions.
• Avoid deep recursion issues on large inputs.
• Do not mutate inputs; return a new sorted output.
• Handle empty or missing inputs without throwing errors.
• Keep runtime close to linear time where possible.
• Prefer a pure function: no side effects beyond the return value.

Mini snippet (usage only)

// Example usage
const root = /* recover a bst with two swapped nodes input */;
const result = recoverBST(root);
console.log(result);

// Edge case check
const empty = root ?? null;
const fallback = recoverBST(root);
console.log(fallback);

// Expected: describe output shape, not the implementation
// (no solution code in preview)

Common pitfalls

• Mutating inputs instead of returning a new value.
• Skipping edge cases like empty input, duplicates, or nulls.
• Overlooking time complexity for large inputs.

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