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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.

Design Food Rating System

Design a food rating system that can update ratings and return the highest-rated food for a specific cuisine.

Medium
Approach 1

Level III: Multi-Index with Sorted Sets (Optimal)

Intuition

Use two HashMaps: one to map food -> (cuisine, rating) and another to map cuisine -> SortedSet of (rating, food). SortedSet handles lexicographical tie-breaks.

Change Rating: O(log N), Highest Rated: O(1).💾 O(N).

Detailed Dry Run

Cuisine 'Japanese' has {Sushi: 5, Ramen: 4}. Update Ramen to 6 -> Highest Rated is now Ramen.

java
import java.util.*;\nclass FoodRatings {\n    class Food implements Comparable<Food> {\n        String name, cuisine; int rating;\n        Food(String n, String c, int r) { name=n; cuisine=c; rating=r; }\n        public int compareTo(Food other) {\n            if (rating != other.rating) return other.rating - rating;\n            return name.compareTo(other.name);\n        }\n    }\n    Map<String, Food> foodMap = new HashMap<>();\n    Map<String, TreeSet<Food>> cuisineMap = new HashMap<>();\n    public FoodRatings(String[] foods, String[] cuisines, int[] ratings) {\n        for(int i=0; i<foods.length; i++) {\n            Food f = new Food(foods[i], cuisines[i], ratings[i]);\n            foodMap.put(foods[i], f);\n            cuisineMap.computeIfAbsent(cuisines[i], k -> new TreeSet<>()).add(f);\n        }\n    }\n    public void changeRating(String food, int newRating) {\n        Food f = foodMap.get(food);\n        cuisineMap.get(f.cuisine).remove(f);\n        f.rating = newRating;\n        cuisineMap.get(f.cuisine).add(f);\n    }\n    public String highestRated(String cuisine) {\n        return cuisineMap.get(cuisine).first().name;\n    }\n}