Design Food Rating System

# System & Data Structure Design Design problems in DSA interviews test your ability to translate requirements into a functional, efficient, and maintainable class structure. Unlike standard algorithmic problems, the focus here is on State Management and API Design. ### Core Principles 1. Encapsulation: Keep data private and expose functionality through well-defined methods. 2. Trade-offs: Every design choice has a cost. Is it better to have $O(1)$ read and $O(N)$ write, or vice versa? 3. State Consistency: Ensure that your internal data structures (e.g., a Map and a List) stay in sync after every operation. ### Common Design Patterns #### 1. HashMap + Doubly Linked List (DLL) The "Gold Standard" for $O(1)$ caching (LRU/LFU). ```text [Head] <-> [Node A] <-> [Node B] <-> [Node C] <-> [Tail] ^ ^ ^ ^ ^ (MRU) (Data) (Data) (Data) (LRU) ``` - HashMap: Provides $O(1)$ lookups for keys to their corresponding nodes. - DLL: Provides $O(1)$ addition/removal of nodes at both ends, maintaining the order of access. #### 2. Amortized Analysis (Rebalancing) Commonly used in Queue using Stacks or Dynamic Arrays. - Instead of doing heavy work on every call, we batch it. Pushing to a stack is $O(1)$, and "flipping" elements to another stack happens only when necessary, averaging $O(1)$ per operation. #### 3. Ring Buffers (Circular Arrays) Used for fixed-size memory management (e.g., Circular Queue, Hit Counter). ```text [0] [1] [2] [3] [4] [5] ^ ^ ^ Head (Data) Tail (Pops) (Next Push) ``` - Use `(index + 1) % capacity` to wrap around the array. #### 4. Concurrency & Thread Safety For "Hard" design problems (e.g., Bounded Blocking Queue). - Use Mutexes (Locks) to prevent data races. - Use Condition Variables (`wait`/`notify`) to manage producer-consumer logic efficiently without busy-waiting. ### How to Approach a Design Problem 1. Identify the API: What methods do you need to implement? (`get`, `put`, `push`, etc.) 2. Define the State: What variables represent the current state? (Size, Capacity, Pointers). 3. Choose the Data Structures: Select the combination that minimizes time complexity for the most frequent operations. 4. Dry Run: Trace the state changes through a sequence of operations based on your chosen structure.