Solve array merge, tree view, and maze tasks
Company: Meta
Role: Machine Learning Engineer
Category: Coding & Algorithms
Difficulty: medium
Interview Round: Onsite
Solve the following coding tasks.
## 1) Merge two sorted arrays in-place
You are given two integer arrays `A` and `B`, each sorted in non-decreasing order.
- `A` has length `m + n`, where the first `m` elements are valid, and the last `n` elements are extra space.
- `B` has length `n`.
**Task:** Modify `A` in-place so that it becomes a single sorted array containing all `m + n` elements.
**Constraints (typical):** `0 ≤ m, n ≤ 2e5`, values fit in 32-bit signed int.
## 2) Right-side view of a binary tree (variant)
Given the root of a binary tree, return the list of node values visible when looking at the tree from the right side (i.e., the last node encountered at each depth when scanning left-to-right).
**Task:** Output the values from top to bottom.
**Constraints (typical):** up to `2e5` nodes.
## 3) Maze problem (multi-part)
You are given a 2D grid representing a maze:
- `'.'` = empty cell, `'#'` = wall
- `'S'` = start, `'E'` = end
- You can move in 4 directions (up/down/left/right) to non-wall cells.
**Tasks:**
A. Determine whether a path exists from `S` to `E`.
B. If a path exists, return the length of the shortest path (number of moves).
C. Optionally, return one shortest path as a string over `{U,D,L,R}`.
**Constraints (typical):** grid size up to `2000 x 2000` (so algorithms should be near-linear in number of cells).
Quick Answer: This question evaluates array manipulation and in-place algorithms, binary tree traversal and visibility reasoning, and grid graph traversal for path existence and shortest paths, reflecting competencies in data structures, algorithmic complexity, and space- and time-efficient implementations.