i Code With Hiren.

  iOS Technical Interview Q&A Guide Architecture Patterns CLEAN Architecture Q: What is CLEAN Architecture? A: CLEAN Architecture is a software design philosophy created by Robert C. Martin that separates an application into layers with clear boundaries. The core principle is that dependencies point inward - outer layers depend on inner layers, never the reverse. Q: What are the layers in CLEAN Architecture? A: From innermost to outermost: Entities : Core business objects and logic Use Cases/Interactors : Application-specific business rules Interface Adapters : Presenters, ViewModels, Controllers Frameworks & Drivers : UI, Database, Network, External APIs Q: Why use CLEAN Architecture? A: Benefits include testability (mock dependencies easily), maintainability (clear separation), flexibility (swap implementations), and independence from frameworks. It's ideal for large, complex applications with multiple developers. Q: What are the disadvantages of CLEAN Arch...

  Complete iOS Interview Guide - Part 1 1. CLEAN Architecture CLEAN Architecture is a software design philosophy that emphasizes separation of concerns and independence of frameworks, UI, and databases. Created by Robert C. Martin (Uncle Bob), it's widely used in iOS development. Core Principles 1. Independence: Independent of frameworks (UIKit, SwiftUI) Independent of UI Independent of database Independent of external agencies Testable without UI, database, or external elements 2. Separation of Concerns: Each layer has a specific responsibility and doesn't know about layers above it. The Layers (from innermost to outermost) Entities (Enterprise Business Rules): Core business objects Most stable, least likely to change Pure Swift objects with no framework dependencies Example: User, Product, Order models // Entity struct User { let id: String let name: String let email: String func isValidEmail() -> Bool { // Business logic ...

  DSA Blog Series - Part 6: Practical Wisdom & Career Topics 🐾  Practical & Career-Oriented Topics 51. How to Approach DSA Problems Systematically Having a systematic approach transforms random problem-solving into a reliable process. Here's a framework that works consistently. The UMPIRE Method: U - Understand the problem Don't rush to code. Spend time understanding: What are the inputs and outputs? What are the constraints? (array size, value ranges, time limits) Are there edge cases? (empty input, single element, duplicates, negative numbers) Can I restate the problem in my own words? Action:  Work through 2-3 examples manually. Include an edge case. M - Match to patterns Ask yourself: Have I seen something similar before? What data structure naturally fits this problem? What algorithm patterns apply? (two pointers, sliding window, DP, graph traversal) What do the constraints tell me? (n ≤ 20 suggests exponential, n ≤ 10^6 suggests O(n log n)) Action:  Id...