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Sohu Tech Products
Sohu Tech Products
Nov 27, 2024 · Mobile Development

Beginner's Guide to iOS Memory Analysis: Virtual Memory, Heap, Autoreleasepool, and Leaks

This beginner‑level guide explains iOS virtual‑memory and heap fundamentals, demonstrates how autorelease‑pool buildup and retain‑cycle leaks cause out‑of‑memory crashes, and shows step‑by‑step use of Xcode’s Memory Graph, Instruments Allocations, and leak detection tools, plus tips on weak versus unowned references.

AutoreleasePoolInstrumentsLeaks
0 likes · 17 min read
Beginner's Guide to iOS Memory Analysis: Virtual Memory, Heap, Autoreleasepool, and Leaks
NetEase Cloud Music Tech Team
NetEase Cloud Music Tech Team
May 18, 2023 · Mobile Development

In‑App Purchase (IAP) Overview and Implementation Guide for iOS

The guide explains Apple’s four in‑app purchase types, how to create and configure products in App Store Connect, implements the StoreKit purchase flow (including product request, payment, transaction observation, and receipt verification on server), addresses common pitfalls, and introduces NetEase’s NEStoreKit wrapper for easier integration.

In-App PurchaseObjective‑CStoreKit
0 likes · 15 min read
In‑App Purchase (IAP) Overview and Implementation Guide for iOS
QQ Music Frontend Team
QQ Music Frontend Team
Apr 19, 2020 · Mobile Development

How to Integrate Flutter Boost into an iOS (Objective‑C) Project

This guide walks through preparing an Xcode project with CocoaPods, adding a Flutter module as a dependency, implementing the required platform router in Objective‑C, binding it in AppDelegate, and using Flutter Boost’s open and present APIs to navigate between native and Flutter pages.

CocoaPodsFlutter BoostHybrid Development
0 likes · 6 min read
How to Integrate Flutter Boost into an iOS (Objective‑C) Project
Hujiang Technology
Hujiang Technology
Jun 18, 2017 · Artificial Intelligence

Using Apple Core ML for On‑Device Machine Learning: A Practical Guide with ResNet‑50 Example

Core ML is Apple’s on‑device machine‑learning framework that integrates deep‑learning, decision‑tree, SVM and linear models into iOS apps, leveraging Accelerate, BNNS and Metal Performance Shaders, and the article demonstrates its use with a ResNet‑50 model, Vision APIs, and complete Objective‑C code.

Artificial IntelligenceCore MLObjective‑C
0 likes · 6 min read
Using Apple Core ML for On‑Device Machine Learning: A Practical Guide with ResNet‑50 Example