Question 1

Design a solution to generate unique device names from a list of IoT devices.

Accepted Answer

**Section 1 — The Context (The 'Why')**
The primary challenge for this design in Python/Coding is balancing scale, cost, and reliability. At scale, naive approaches fail: single points of failure cause cascades, schema evolution breaks consumers, and over-provisioning explodes cost. Failure modes include silent data loss from non-idempotent writes, cascading job failures from tight coupling, and operational burden from manual intervention....

Question 2

Extended the solution to determine the nth largest element in an array.

Accepted Answer

**Quickselect:** Partition like quicksort; recurse one side. O(n) avg. **Heap:** Size n; pop to get nth. O(n log n). **Sort:** O(n log n). **When:** Small n→partial sort. **Why:** Avoid full sort when possible.

Question 3

Given the Infix, Prefix, or Postfix notation of an expression, write the code to compute the final result.

Accepted Answer

**Postfix:** Stack; number→push; operator→pop two, compute, push. **Prefix:** Right→left, same. **Infix:** Shunting yard or recursive descent. **Why:** Parser foundation. **Production:** Handle precedence.

Question 4

Implement an algorithm to find the longest ordered subsequence of vowels in a given string.

Accepted Answer

**Why This Pattern Matters:** Subsequence DP is foundational for sequence alignment, log parsing (ordered event sequences), and NLP token sequences.

**Architectural Logic:** We track the longest valid subsequence ending at each vowel (a→e→i→o→u). State: dp[v] = max length ending at vowel v. Transition: when we see vowel v, we can extend from prev vowel. O(n) time, O(1) space—five vowel states.

**Scalability:** Linear scan, no extra structures—suitable for streaming....

Question 5

Solve for the Kth smallest element in a Binary Search Tree.

Accepted Answer

**Why BST Kth Smallest:** In-order traversal yields sorted order. kth smallest = kth node in in-order. Used in top-K from sorted structure, percentile queries.

**Approach:** (1) In-order with counter: O(h + k) time. (2) Augmented BST: each node stores subtree size—O(h) search by comparing k with left size.

**Scalability:** BST in-memory; for disk-backed (B-tree), similar logic....

Question 6

Write code to calculate the power of a given number in minimum time complexity.

Accepted Answer

**Binary Exponentiation:** x^n in O(log n). x^8 = ((x^2)^2)^2. While n: if n odd, result*=x; x*=x; n//=2.

def power(x, n):
    if n < 0: return 1/power(x, -n)
    res = 1
    while n:
        if n & 1: res *= x
        x *= x
        n >>= 1
    return res

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