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The Trade Desk·Software Engineer·Technical Phone Screen·Intermediate

Intermediate
Apr 2026

Summary

Interviewed for a SWE role at The Trade Desk and got a system design question about extending an LRU cache with a custom eviction policy. Pretty niche problem, felt like it was testing whether you actually understood the internals rather than just knowing the textbook definition.

Questions Asked (1)

Q1

Design a custom policy extension for an LRU Cache. How would you modify or extend the standard implementation to support pluggable or configurable eviction strategies?

System DesignAlgorithms & Data StructuresTechnical Trade-offs
Author's notes

My first instinct was to just describe a doubly linked list plus hashmap setup, which is the standard answer, but that wasn't really the point.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements: what does 'pluggable' mean (runtime vs compile-time, per-cache vs global)? Then propose a design that separates the eviction policy from the cache storage and access logic, using interfaces and dependency injection. Discuss trade-offs like performance overhead, thread safety, and how to handle policy-specific metadata.

Pro tip: Mention that you would keep the core cache operations (get/put) policy-agnostic and use a strategy pattern, but also consider using a policy that can maintain its own data structures (e.g., for LFU) without bloating the cache. This shows you understand separation of concerns and performance implications.

1. Clarify Requirements and Scope

Ask questions to understand what 'pluggable' means: should policies be swappable at runtime? Per-cache instance or global? What are the performance and thread-safety requirements? This ensures you design the right solution.

2. Define an Eviction Policy Interface

Propose an interface (e.g., EvictionPolicy) with methods like onGet(key), onPut(key, value), evict(), and possibly remove(key). This abstracts the policy from the cache.

3. Design the Cache to Delegate to the Policy

The cache should handle storage (e.g., a map) and delegate eviction decisions to the policy. The policy may need access to cache metadata (e.g., access order) or maintain its own structures.

4. Implement Concrete Policies

Show how LRU, LFU, FIFO, etc., can be implemented as separate classes implementing the interface. For LRU, use a doubly linked list + hashmap; for LFU, use frequency buckets.

5. Discuss Trade-offs and Extensions

Address performance overhead (e.g., extra method calls), thread safety (synchronization or concurrent data structures), and how to configure policies (factory, dependency injection, or configuration file).

Key Points to Mention

  • Strategy pattern and dependency injection to make policies pluggable.
  • Interface segregation: policy should not need to know about cache internals beyond necessary metadata.
  • Performance considerations: overhead of delegation, memory footprint of policy-specific data structures.
  • Thread safety: ensuring policy and cache operations are atomic, possibly using locks or concurrent collections.
  • Configuration mechanisms: how policies are selected (e.g., builder pattern, factory, or config).
  • Extensibility: allowing custom policies without modifying core cache code.

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