DRY (Don't Repeat Yourself) in LLD - System Design Exercise

Design: DRY Principle Implementation in Software Design

Focus on design patterns and architecture to enforce DRY in code and system components. Out of scope: specific programming language syntax or IDE tooling.

Functional Requirements

FR1: Avoid code duplication across the system

FR2: Ensure maintainability by centralizing repeated logic

FR3: Support easy updates without changing multiple places

FR4: Promote reusability of components and modules

Non-Functional Requirements

NFR1: System should handle up to 1000 concurrent users

NFR2: Code changes should propagate with minimal risk of bugs

NFR3: Latency impact of abstraction layers should be minimal (<5ms overhead)

NFR4: Maintain 99.9% uptime for critical services

Think Before You Design

Questions to Ask

❓ Question 1

❓ Question 2

❓ Question 3

❓ Question 4

Key Components

Reusable modules or libraries

Service layers or APIs

Configuration management

Shared databases or caches

Design Patterns

Modularization

Service-Oriented Architecture (SOA)

Template Method pattern

Decorator pattern

Inheritance and composition

Reference Architecture

  +-------------------+       +-------------------+       +-------------------+
  |  Client Layer     | <---> |  Service Layer    | <---> |  Shared Modules   |
  +-------------------+       +-------------------+       +-------------------+
                                   |                             |
                                   v                             v
                          +-------------------+         +-------------------+
                          |  Database Layer   |         |  Configuration    |
                          +-------------------+         +-------------------+

Components

Client Layer

Any frontend or API client

Consume services without duplicating business logic

Service Layer

REST/gRPC services or application logic modules

Centralize business logic to avoid repetition

Shared Modules

Reusable libraries or packages

Provide common utilities and helpers used across services

Database Layer

Relational or NoSQL database

Store data centrally to avoid duplication

Configuration

Central config management (e.g., Consul, etcd)

Manage shared settings to prevent repeated hardcoded values

Request Flow

1. Client sends request to Service Layer

2. Service Layer calls Shared Modules for common logic

3. Service Layer queries Database Layer for data

4. Service Layer uses Configuration service for settings

5. Service Layer returns response to Client

Database Schema

Entities: User, Product, Order Relationships: - User 1:N Order - Order N:1 Product All shared data stored centrally to avoid duplication in multiple places.

Scaling Discussion

Bottlenecks

Shared modules becoming a single point of failure

Service Layer overloaded with requests

Database contention due to centralized data

Configuration service latency impacting startup or runtime

Solutions

Deploy shared modules as distributed libraries or microservices with redundancy

Use load balancers and horizontal scaling for Service Layer

Implement database sharding and caching layers

Use highly available configuration stores with local caching

Interview Tips

Time: 10 minutes to clarify requirements and constraints, 20 minutes to design architecture and data flow, 15 minutes to discuss scaling and trade-offs

Explain the importance of avoiding code duplication for maintainability

Describe how centralizing logic reduces bugs and eases updates

Discuss trade-offs between DRY and over-abstraction

Highlight how shared modules and configuration help enforce DRY

Address scaling challenges and solutions for centralized components