← Molocoads Interview Insights

Molocoads·Software Engineer·Technical Phone Screen·Intermediate

Intermediate
Jun 2026

Summary

Did a coding round for a Software Engineer role at Molocoads with two algorithm problems. Nothing too wild, but the second one had me second-guessing my approach the whole time.

Questions Asked (2)

Q1

Given a list of rooms where each room contains keys to other rooms, determine whether you can visit all rooms starting from room 0.

Algorithms & Data Structures
Author's notes

Graph traversal problem basically.

Create a free account to read the full note

AI HintsAI Generated

Suggested Approach

Model the rooms as a directed graph where each room is a node and keys are edges to other rooms. Use DFS or BFS starting from room 0 to traverse all reachable rooms, then check if the number of visited rooms equals the total number of rooms.

Pro tip: Clarify edge cases upfront, such as empty input or rooms with no keys, and mention that you'd handle them gracefully. Also, discuss the trade-offs between DFS (recursive vs iterative) and BFS, showing awareness of stack overflow risks and memory usage.

1. Understand the problem

Restate the problem to ensure clarity: given a list of lists where rooms[i] contains keys to other rooms, determine if all rooms can be visited starting from room 0. Confirm assumptions like room 0 is always the start and keys are unique.

2. Model as a graph

Explain that each room is a node and each key is a directed edge from the current room to the key's room. This transforms the problem into checking if all nodes are reachable from node 0.

3. Choose traversal algorithm

Select DFS or BFS to explore reachable rooms. DFS can be implemented recursively or iteratively; BFS uses a queue. Mention that both have O(N+E) time and O(N) space, where N is number of rooms and E is total keys.

4. Implement traversal and track visited

Use a visited set or boolean array to avoid cycles. Start from room 0, add it to visited, and process its keys, adding unvisited rooms to the traversal structure. Continue until no more rooms can be visited.

5. Check completeness and discuss edge cases

After traversal, compare the size of visited with total rooms. If equal, return true; else false. Discuss edge cases: empty list (return true if 0 rooms? clarify), room with no keys, disconnected rooms, and self-loops.

Key Points to Mention

  • Graph representation: rooms as nodes, keys as directed edges
  • DFS vs BFS: trade-offs and typical implementation
  • Time and space complexity: O(N+E) time, O(N) space
  • Cycle detection: using visited set to avoid infinite loops
  • Edge cases: empty input, room 0 with no keys, unreachable rooms
  • Correctness: all rooms visited iff graph is connected from node 0

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.

Q2

Given a balanced parentheses string, compute its score using the rules: "()" = 1, concatenation adds scores, and wrapping a string in parens doubles its score.

Algorithms & Data Structures
Author's notes

This one messed with me more than I expected.

Create a free account to read the full note

AI HintsAI Generated

Suggested Approach

Start by clarifying the problem and walking through a simple example to ensure understanding. Then, discuss both stack-based and depth-counting approaches, explaining their time and space complexities. Finally, implement the chosen approach with clean code and test with edge cases.

Pro tip: Mention that the score can be computed in O(n) time and O(1) space using a depth-counting method, which is optimal. This shows you think about efficiency beyond the obvious stack solution.

1. Understand the problem

Restate the rules and confirm with the interviewer. Walk through a small example like '(()(()))' to ensure alignment.

2. Explore approaches

Discuss stack-based simulation and the more optimal depth-counting method. Compare their time and space complexities.

3. Implement the solution

Write clean code for the chosen approach, handling edge cases like empty string and deeply nested parentheses.

4. Test and validate

Run through provided examples and edge cases, verifying correctness and performance.

Key Points to Mention

  • Stack-based simulation: push scores, handle concatenation and nesting.
  • Depth-counting optimization: track depth and add 2^depth when encountering '()'.
  • Time complexity: O(n) for both approaches.
  • Space complexity: O(n) for stack, O(1) for depth-counting.
  • Edge cases: empty string, single pair, deeply nested, concatenated pairs.
  • Recursive definition and potential for recursion (though iterative is better).

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.