Design problems in data structures and algorithms test your ability to build scalable, efficient systems using the right combination of data structures. Instead of solving a single algorithmic step, these questions ask you to design classes, APIs, or data structures that support multiple operations efficiently. They are extremely common in coding interviews at top tech companies because they reveal how well you understand trade-offs, time complexity, and real-world problem modeling.

Typical design problems include building structures such as LRU caches, rate limiters, randomized collections, or streaming data processors. Solving them often requires combining multiple core topics like Hash Table for fast lookups, Heap (Priority Queue) for prioritization, or Queue for ordered processing. In some cases, structural relationships rely on Linked List operations to maintain constant-time updates.

Common patterns in design questions include:

• Combining multiple data structures to achieve optimal time complexity
• Maintaining state efficiently across operations
• Handling streaming or dynamic data
• Designing APIs with clear responsibilities and constraints

With 123 carefully selected practice problems, this section will help you strengthen your ability to architect efficient data structures and confidently tackle complex design questions in technical interviews.