How do you approach debugging a system you did not build?

When debugging an unfamiliar system, I start by understanding the high level architecture and the data flow between components.

Next, I reproduce the issue in a controlled environment and use logs, metrics, and traces to narrow down where the failure occurs. I form hypotheses and validate them incrementally rather than making broad changes.

Throughout the process, I document findings and communicate with team members who have context. This structured approach helps reduce guesswork and speeds up root cause identification.

Tell me about a time you failed.

How would you detect a memory leak in a production system?

I would start by monitoring memory usage trends over time using application metrics and system level tools. A steadily increasing memory footprint without release is usually a strong signal.

Next, I would capture heap dumps or use profiling tools to identify objects that are not being garbage collected. From there, I would trace back to the code paths retaining those references.

After fixing the root cause, I would add monitoring and alerts to detect abnormal memory growth early in the future. Prevention through observability is just as important as the fix itself.

How would you design a cache system?

I would begin by clarifying access patterns, data volatility, and consistency requirements.

At a high level, the system would include a fast in-memory cache layer such as Redis in front of the primary database. I would define an eviction policy like LRU to manage memory usage and implement TTLs for data freshness.

I would also plan for cache invalidation strategies, cache stampede protection, and monitoring of hit rate. The design trade-off typically balances freshness, consistency, and performance.

Something here is wrong.

Tell me about a time you disagreed with a teammate.

In a previous project, we disagreed on introducing a new caching layer. I raised concerns about cache invalidation complexity and proposed we measure current latency first. We ran benchmarks together and agreed on a simpler optimization that met our needs.

Explain a project you are proud of.

I built a booking system that reduced manual processing. I designed the API with Express and optimized database queries with indexing. As a result, average response time dropped from 900 ms to 180 ms and the system handled 3x more concurrent users.

Explain how a hash map works internally.

A hash map stores key value pairs by applying a hash function to the key to compute an index in an underlying array. Ideally, the hash function distributes keys uniformly to minimize collisions.

When collisions occur, common strategies include chaining using linked lists or open addressing. Lookups, insertions, and deletions are O(1) on average but can degrade toward O(n) in worst case collision scenarios.

In modern implementations like Java’s HashMap, when collision chains grow beyond a threshold, they may be converted into balanced trees to maintain efficient performance.

What happens when you type a URL into the browser?

When a URL is entered, the browser first checks its cache and then performs DNS resolution to translate the domain name into an IP address.

Next, the browser establishes a TCP connection with the server, followed by a TLS handshake if the connection is HTTPS. The browser then sends an HTTP request to the server.

The server processes the request and returns an HTTP response. Finally, the browser parses the HTML, constructs the DOM and CSSOM, executes JavaScript if present, and renders the page to the screen.