Fetch, group, and print paginated activities
Company: Peregrine
Role: Software Engineer
Category: Coding & Algorithms
Difficulty: medium
Interview Round: Technical Screen
##### Question
Given a paginated API that returns (totalCount, activities[]) for a requested page, implement code that iterates through all pages and prints every activity. After fetching all activities, group them into clumps where each clump contains activities sharing the same type and name. Implement a Clump class with attributes: activities list, type, and name, and return the clumps. Update the output so each activity shows the user’s name (retrieved from a separate getUserName(userId) API) instead of the user ID.
Quick Answer: This interview question evaluates algorithm design, data structures, correctness, complexity, edge cases, and implementation details in a realistic interview setting. A strong answer for Fetch, group, and print paginated activities states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Solution
# Solution Alignment
The prompt asks for an implementation-level answer. The safest way to present it is to define the state, maintain clear invariants, then walk through complexity and tests.
## Problem Restatement
##### Question Given a paginated API that returns (totalCount, activities[]) for a requested page, implement code that iterates through all pages and prints every activity. After fetching all activities, group them into clumps where each clump contains activities sharing the same type and name. Implement a Clump class with attributes: activities list, type, and name, and return the clumps. Update the output so each activity shows the user’s name (retrieved from a separate getUserName(userId) API) instead of the user ID.
## Recommended Approach
Start with a brute-force baseline to confirm correctness, then identify the repeated work or ordering property that enables a better data structure such as a hash map, heap, stack, queue, two pointers, prefix sums, BFS/DFS, or dynamic programming. Write the implementation around a small invariant and test that invariant directly.
## Correctness
The implementation should maintain an invariant after each loop or operation that directly matches the problem statement. At termination, that invariant implies the returned value has considered every valid candidate exactly once, or has preserved the required data-structure state after every API call.
## Complexity
State the baseline complexity and the optimized complexity. For most interview constraints, justify why the optimized approach meets the expected input size.
## Edge Cases and Tests
Empty and singleton inputs, duplicates, ties, invalid inputs, boundary values, and tests that exercise the main invariant.