Start by clarifying requirements and assumptions (e.g., tie-breaking, data volume, caching) before diving into the design. Then walk through each layer—entity, repository, service, controller—explaining your choices and trade-offs, and finish with a testing strategy that covers unit, integration, and edge cases.
Pro tip: Demonstrate production awareness by discussing how you'd handle ties deterministically (e.g., secondary sort by course ID) and how you'd optimize the aggregation query for large datasets (e.g., using a database view or caching).
Ask about tie-breaking rules, expected data volume, and whether the result should be cached or computed on-demand. State your assumptions clearly to show you think before coding.
Define Course and Enrollment entities with appropriate relationships (e.g., @OneToMany) and JPA annotations. Explain how you'd map the schema and handle bidirectional vs. unidirectional associations.
Create a Spring Data JPA repository with a custom aggregation query (using @Query or a projection) to fetch the most popular course. In the service layer, apply tie-breaking logic and handle exceptions.
Expose a GET endpoint that returns the course as JSON. Use @ControllerAdvice to handle errors (e.g., no courses found) and return appropriate HTTP status codes.
Describe unit tests for the service (mocking the repository), integration tests for the repository (using @DataJpaTest), and end-to-end tests for the controller (using MockMvc). Include edge cases like ties and empty results.
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