DEV Community: Rajesh Mishra

Java 25 foreign function and memory API tutorial with examples — Complete Guide

Rajesh Mishra — Mon, 31 Aug 2026 07:18:36 +0000

Java 25 foreign function and memory API tutorial with examples — Complete Guide

A practical, in-depth guide to Java 25 foreign function and memory API tutorial with examples with examples.

INTRO

Every time you need to call a C library from Java you’re forced into the world of JNI: verbose boilerplate, fragile native headers, and a runtime that feels like a black box. The pain isn’t just syntactic—debugging crashes, managing lifetimes of native memory, and keeping the Java‑to‑native contract in sync become daily headaches. As a result, many teams either avoid native code altogether or ship a custom JNI wrapper that quickly becomes a maintenance nightmare.

Java 25 finally gives us a clean, type‑safe alternative: the Foreign Function & Memory (FFM) API, the culmination of Project Panama. It lets you describe native symbols, allocate off‑heap memory, and invoke functions without writing a single line of C or dealing with System.loadLibrary. The API is designed to be ergonomic, performant, and, most importantly, safe enough to be used in production services that cannot afford occasional segmentation faults.

If you’ve been watching the preview releases and wondering when the “real thing” lands, this article is your invitation to start experimenting now. The full guide walks you through the entire workflow—from setting up the JDK preview to wiring up a complex native struct—so you can replace brittle JNI code with concise, maintainable Java.

WHAT YOU'LL LEARN

How to enable the Java 25 preview and import the java.foreign module.
Defining and loading native symbols with Linker and SymbolLookup.
Allocating, reading, and writing off‑heap memory using MemorySegment and MemoryLayout.
Mapping C structs to Java records for seamless field access.
Handling callbacks and function pointers from Java to native code.
Performance considerations and common pitfalls when mixing managed and unmanaged memory.

A SHORT CODE SNIPPET

import java.foreign.*;
import java.lang.invoke.*;

public class SimpleFFM {
public static void main(String[] args) throws Throwable {
// Load the C standard library (libc) and look up strlen
SymbolLookup libc = SymbolLookup.libraryLookup("c", MemorySegment.globalScope());
MethodHandle strlen = Linker.nativeLinker()
.downcallHandle(libc.lookup("strlen").orElseThrow(),
FunctionDescriptor.of(ValueLayout.JAVA_LONG, ValueLayout.ADDRESS));

// Allocate a native UTF‑8 string
MemorySegment hello = CLinker.toCString("Hello, FFM!", StandardCharsets.UTF_8);

// Call the native strlen and print the result
long length = (long) strlen.invokeExact(hello);
System.out.println("Length = " + length);
}
}

This minimal example demonstrates the core workflow: locate a native function, prepare its signature, allocate off‑heap data, and invoke it—all in pure Java.

KEY TAKEAWAYS

The FFM API replaces JNI with a declarative, type‑safe approach that lives entirely in Java code.
MemorySegment and MemoryLayout give you fine‑grained control over native memory without manual malloc/free.
Function descriptors let the linker verify argument and return types at compile time, reducing runtime crashes.
Proper scope management (e.g., using MemorySegment.globalScope() vs. confined scopes) is essential to avoid memory leaks.

👉 Read the complete guide with step-by-step examples, common mistakes, and production tips:

Java 25 foreign function and memory API tutorial with examples — Complete Guide

Mastering GitHub Copilot Workspace: Multi-File AI Edits Tutorial (2026)

Rajesh Mishra — Sun, 30 Aug 2026 08:05:15 +0000

This is a summary of the full tutorial published on howtostartprogramming.in.

TL;DR GitHub Copilot Workspace (released 2026) lets you run a single AI‑powered session that can read, understand, and edit multiple files across a repo in real time. Set it up in three steps, then start issuing multi‑file commands like “refactor this service layer” or “add logging to every controller”. The result is faster, more consistent code changes with fewer context switches. Key Steps to Get Started Install the extension (VS Code or JetBrains) and enable Copilot Workspace in settings. Initialize a workspace for your project folder. Give the AI the right scope – select the files/folders you want it to edit. One‑liner setup (EnlighterJS) # Install the latest Copilot extension code --install-extension GitHub.copilot # Open your repo and start a workspace code . && copilot workspace ini

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🔗 GitHub Copilot workspace tutorial multi-file AI edits 2026 — Full Guide with Code Examples

The full article includes:

✅ Step-by-step code examples (copy-paste ready)
✅ Complete working project (Spring Boot / Java)
✅ Common mistakes + fixes
✅ Production tips and benchmarks
✅ FAQ section

Published on How to Start Programming — practical AI and Java tutorials for developers.

latest Java collections framework tutorial with examples — Complete Guide

Rajesh Mishra — Sat, 29 Aug 2026 07:10:20 +0000

latest Java collections framework tutorial with examples — Complete Guide

A practical, in-depth guide to latest Java collections framework tutorial with examples with examples.

INTRO

Every production‑grade Java codebase eventually hits the point where you need to store, retrieve, and manipulate groups of objects. The default go‑to is often ArrayList or a plain HashMap, but as soon as you start caring about concurrency, ordering guarantees, or memory footprint, the naïve choices become liabilities. Miss‑using a collection can lead to hidden performance bottlenecks, subtle bugs, and a maintenance nightmare that only surfaces under load.

The Java Collections Framework (JCF) has evolved dramatically in recent JDK releases—think record‑based immutable collections, the new Stream‑friendly Collectors.toUnmodifiableList(), and the java.util.concurrent enhancements that make lock‑free programming more approachable. Yet the official docs are dense, and most tutorials stop at “how to add an element”. What you really need is a concise, example‑driven walkthrough that shows when to pick EnumMap over HashMap, why CopyOnWriteArrayList shines in read‑heavy scenarios, and how the new factory methods can replace boilerplate builders in a single line.

In this teaser, I’ll surface the pain points that the full guide resolves: choosing the right collection for the right job, avoiding common pitfalls like accidental mutability, and writing code that scales from a single‑threaded prototype to a multi‑core service without a rewrite.

WHAT YOU'LL LEARN

The decision matrix for selecting List, Set, Map, and Queue implementations based on ordering, uniqueness, and concurrency requirements.
How Java 17+ immutable collection factories (List.of, Set.of, Map.ofEntries) simplify defensive copying and thread‑safety.
Real‑world patterns for using EnumMap, IdentityHashMap, and WeakHashMap to solve memory‑leak and identity‑based lookup problems.
A deep dive into the concurrent package: ConcurrentHashMap, CopyOnWriteArrayList, BlockingQueue, and when to prefer StampedLock over synchronized.
Performance benchmarking tricks with JMH to validate that your collection choice actually improves latency and throughput.
Common mistakes—like mutating a collection returned by Collections.unmodifiableList or forgetting to rehash after bulk updates—and how to avoid them in production code.

A SHORT CODE SNIPPET

import java.util.*;
import java.util.concurrent.*;

public class Demo {
public static void main(String[] args) {
// Immutable list created in one line (Java 17+)
List<String> colors = List.of("red", "green", "blue");

// Thread‑safe map with computeIfAbsent for lazy value creation
ConcurrentMap<Integer, String> cache = new ConcurrentHashMap<>();
String value = cache.computeIfAbsent(42, k -> fetchFromDb(k));

System.out.println(colors);
System.out.println("Cached value: " + value);
}

private static String fetchFromDb(Integer key) {
// Simulate expensive operation
return "value-" + key;
}
}

The snippet demonstrates two modern practices: using the immutable factory method to avoid accidental mutation, and leveraging ConcurrentHashMap.computeIfAbsent to safely populate a shared cache without explicit locks.

KEY TAKEAWAYS

Pick the right abstraction first – the collection’s contract (ordering, uniqueness, thread‑safety) should drive the implementation, not the other way around.
Immutable factories are not just syntactic sugar; they provide built‑in safety guarantees that eliminate a whole class of concurrency bugs.
Concurrent collections are purpose‑built – CopyOnWriteArrayList excels when reads vastly outnumber writes, while ConcurrentHashMap offers lock‑striped scalability for mixed workloads.
Benchmark before you assume – small changes in collection choice can swing latency by orders of magnitude; JMH is the gold standard for proving it.

👉 Read the complete guide with step-by-step examples, common mistakes, and production tips:
latest Java collections framework tutorial with examples — Complete Guide

10 Ways to Use AI Tools to 10x Developer Productivity in 2026

Rajesh Mishra — Fri, 28 Aug 2026 11:45:32 +0000

This is a summary of the full tutorial published on howtostartprogramming.in.

TL;DR – 10 AI‑Powered Hacks to 10× Your Development Workflow in 2026 Grab the cheat‑sheet below, copy the starter scripts, and plug the listed tools into your daily routine. You’ll see measurable speed‑ups within a single sprint. # AI Strategy Expected Impact Tool(s) to Deploy 1 AI‑augmented code completion (context‑aware) 30‑50% fewer keystrokes GitHub Copilot X, Tabnine Enterprise, Cursor 2 Instant test‑case generation 40% faster test coverage expansion DeepCode TestGen, OpenAI Codex (prompt “write Jest tests for …”) 3 AI‑driven bug triage & auto‑fix suggestions 60% reduction in MTTR Sentry AI, CodeQL + LLM, GitHub Advanced Security 4 Natural‑language to API scaffolding 2‑3× faster endpoint creation OpenAI Function‑Calling, LangChain API‑Wizard 5 AI‑powered refactoring & linting 25% less

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🔗 10 ways to use AI tools to 10x developer productivity 2026 — Full Guide with Code Examples

The full article includes:

✅ Step-by-step code examples (copy-paste ready)
✅ Complete working project (Spring Boot / Java)
✅ Common mistakes + fixes
✅ Production tips and benchmarks
✅ FAQ section

Published on How to Start Programming — practical AI and Java tutorials for developers.

AI code review with GitHub Copilot Chat for Spring Boot projects 2026 — Complete Guide 2026

Rajesh Mishra — Wed, 26 Aug 2026 08:13:25 +0000

This is a summary of the full tutorial published on howtostartprogramming.in.

Introduction In 2026, GitHub Copilot Chat has evolved from a helpful autocomplete into a full‑featured AI code reviewer that can understand, critique, and refactor entire Spring Boot applications. This introduction gives you a quick overview of how the new Copilot Chat workflow fits into a typical Spring Boot development pipeline, what kinds of insights you can expect, and why it’s becoming a must‑have tool for Java teams. Capability What Copilot Chat Does Benefit for Spring Boot Static analysis & style enforcement Detects violations of Google Java Format , Checkstyle , and Spring‑specific conventions. Keeps codebase consistent, reduces review friction. Security & dependency audit Flags vulnerable libraries, suggests safer alternatives, and recommends proper use of @Validated and SecurityF

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🔗 AI code review with GitHub Copilot Chat for Spring Boot projects 2026 — Full Guide with Code Examples

The full article includes:

✅ Step-by-step code examples (copy-paste ready)
✅ Complete working project (Spring Boot / Java)
✅ Common mistakes + fixes
✅ Production tips and benchmarks
✅ FAQ section

Published on How to Start Programming — practical AI and Java tutorials for developers.

Java multithreading and concurrency interview questions with answers — Complete Guide

Rajesh Mishra — Tue, 25 Aug 2026 07:20:47 +0000

Java multithreading and concurrency interview questions with answers — Complete Guide

A practical, in-depth guide to Java multithreading and concurrency interview questions with answers with examples.

INTRO

Every senior‑level Java interview throws a curveball about threads, locks, and the Java Memory Model. Candidates who have only written a “HelloThread” program quickly discover that interviewers expect a deeper grasp of why a piece of code can deadlock, race, or silently corrupt data. The real problem isn’t memorizing API signatures; it’s being able to reason about concurrency, spot subtle bugs, and choose the right abstraction under pressure.

In the wild, production services that mishandle thread pools or misuse volatile end up with intermittent latency spikes or data loss—issues that are notoriously hard to reproduce. A solid interview preparation guide that couples theory with battle‑tested code examples saves you from vague answers and equips you with concrete, production‑ready knowledge you can actually apply on the job.

WHAT YOU'LL LEARN

The lifecycle of a Java thread and how the scheduler interacts with the JVM.
When to use synchronized, Lock implementations, and higher‑level executors.
The nuances of the Java Memory Model: volatile, final, and happens‑before guarantees.
Classic interview riddles (deadlock, livelock, starvation) and step‑by‑step explanations.
How to diagnose and fix common concurrency bugs using tools like ThreadMXBean and jstack.
Real‑world patterns (producer‑consumer, fork‑join, CompletableFuture) that often appear in senior‑level questions.

A SHORT CODE SNIPPET

import java.util.concurrent.CountDownLatch;

public class LatchDemo {
private static final int THREADS = 3;
private static final CountDownLatch latch = new CountDownLatch(THREADS);

public static void main(String[] args) throws InterruptedException {
for (int i = 1; i <= THREADS; i++) {
final int id = i;
new Thread(() -> {
System.out.println("Worker " + id + " started");
// Simulate work
try { Thread.sleep(100 * id); } catch (InterruptedException ignored) {}
System.out.println("Worker " + id + " finished");
latch.countDown(); // signal completion
}).start();
}

System.out.println("Main thread waiting for workers...");
latch.await(); // block until count reaches zero
System.out.println("All workers done – proceeding");
}
}

This tiny program demonstrates a common interview topic: coordinating multiple threads without busy‑waiting. CountDownLatch provides a clear, thread‑safe way to block the main thread until all workers finish, illustrating the happens‑before relationship that the Java Memory Model guarantees.

KEY TAKEAWAYS

Visibility matters: volatile only guarantees visibility and ordering for a single variable; for compound actions you still need atomic constructs or locks.
Choose the right abstraction: Low‑level synchronized is simple but can be a performance bottleneck; ReentrantLock offers flexibility, while executor services handle thread‑pool management for you.
Deadlocks are predictable: By drawing a resource‑allocation graph you can spot cycles before they manifest, a technique interviewers love to see you explain.
Testing concurrency is non‑deterministic: Use stress‑testing tools (jcstress, ThreadMXBean) and deterministic constructs (CountDownLatch, CyclicBarrier) to turn flaky bugs into reproducible tests.

👉 Read the complete guide with step-by-step examples, common mistakes, and production tips:

Java multithreading and concurrency interview questions with answers — Complete Guide

Mastering Amazon Q Developer: A 2026 Java & AWS Guide for Developers

Rajesh Mishra — Mon, 24 Aug 2026 08:15:29 +0000

This is a summary of the full tutorial published on howtostartprogramming.in.

TL;DR Amazon Q Developer is Amazon’s AI‑assisted coding platform that now ships with native Java SDKs, IDE extensions, and serverless integration. In 2026 it lets Java developers generate, test, and secure code — all from within their favorite tools – accelerating delivery by up to 3× while keeping compliance with AWS Well‑Architected standards. What It Does Why It Matters (2026) Generates boilerplate (Spring Boot, Quarkus, Lambda handlers) Reduces repetitive coding, freeing time for business logic. Suggests optimal AWS SDK calls (e.g., S3Client , DynamoDbEnhancedClient ) Ensures best‑practice usage of the latest AWS services and IAM policies. Runs unit & integration tests in‑IDE via QTest Catch bugs before CI, cutting pipeline latency. Security & compliance linting (PCI, HIPAA, GDPR) Auto

📖 Read the Full Tutorial

🔗 Amazon Q Developer tutorial for Java and AWS developers 2026 — Full Guide with Code Examples

The full article includes:

✅ Step-by-step code examples (copy-paste ready)
✅ Complete working project (Spring Boot / Java)
✅ Common mistakes + fixes
✅ Production tips and benchmarks
✅ FAQ section

Published on How to Start Programming — practical AI and Java tutorials for developers.

Spring Boot testing interview questions JUnit Mockito 2026 — Complete Guide

Rajesh Mishra — Sun, 23 Aug 2026 07:16:29 +0000

Spring Boot testing interview questions JUnit Mockito 2026 — Complete Guide

A practical, in-depth guide to Spring Boot testing interview questions JUnit Mockito 2026 with examples.

INTRO

Hiring managers are no longer satisfied with vague answers about “unit testing” or “mocking”. In 2026 the expectation is that a Spring Boot developer can spin up a slice of the application context, isolate beans with Mockito, and verify behavior without pulling in the whole server. The real problem is the gap between textbook knowledge and the hands‑on expertise needed to write reliable, fast tests that survive refactors and CI pipelines.

If you’ve ever stumbled on a “Why does my @WebMvcTest fail when I add a new @Component?” or “How do I mock a bean that’s created by @ConfigurationProperties?” you know the pain. This article teases the most common interview scenarios and shows why mastering the modern Spring Boot testing stack—JUnit 5, Mockito 4+, and the Spring TestContext framework—is a career‑level skill.

WHAT YOU'LL LEARN

How to choose the right test slice (@WebMvcTest, @DataJpaTest, @SpringBootTest) for each interview question.
The latest Mockito extensions for Spring Boot 3.x, including @MockBean vs. @SpyBean and constructor injection tricks.
Strategies to test asynchronous code and @Scheduled tasks without flakiness.
How to validate @ConfigurationProperties binding and profile‑specific beans in isolation.
Common pitfalls with TestEntityManager, transaction rollbacks, and embedded databases.
Real‑world patterns for verifying REST controllers, service layers, and custom Spring extensions.

A SHORT CODE SNIPPET

@SpringBootTest
@ActiveProfiles("test")
class OrderServiceTest {

@MockBean
private PaymentGateway paymentGateway;

@Autowired
private OrderService orderService;

@Test
void shouldCreateOrderAndChargePayment() {
// Arrange
OrderDto dto = new OrderDto("product-123", 2);
when(paymentGateway.charge(any())).thenReturn(PaymentResult.success());

// Act
Order order = orderService.placeOrder(dto);

// Assert
assertNotNull(order.getId());
verify(paymentGateway).charge(argThat(req ->
req.getAmount() == dto.quantity() * 49.99));
}
}

The snippet demonstrates a full‑stack test that boots the Spring context, replaces an external dependency with a Mockito mock, and verifies interaction—all in a single, readable method.

KEY TAKEAWAYS

Selecting the proper test slice reduces startup time and isolates the unit under test, a point interviewers love to probe.
@MockBean works at the Spring container level, letting you replace beans without altering production code.
Always assert on both state (e.g., persisted entity) and behavior (e.g., mock interactions) to cover the full testing pyramid.
Profile‑specific configuration and @ConfigurationProperties can be validated with @TestConfiguration and @DynamicPropertySource to avoid hidden bugs.

👉 Read the complete guide with step-by-step examples, common mistakes, and production tips:

Spring Boot testing interview questions JUnit Mockito 2026 — Complete Guide

Cursor AI IDE tutorial for Java developers complete guide 2026 — Complete Guide 2026

Rajesh Mishra — Sat, 22 Aug 2026 08:05:24 +0000

This is a summary of the full tutorial published on howtostartprogramming.in.

Introduction Welcome to the Cursor AI IDE tutorial for Java developers – Complete Guide 2026 . This article walks you through everything you need to know to boost your productivity with Cursor AI, the AI‑powered integrated development environment that understands Java code, suggests context‑aware completions, and automates repetitive tasks. Whether you are a seasoned Java engineer or just starting out, this guide will help you set up the environment, explore its core features, and integrate AI assistance into your daily workflow. What you will learn Section Key Topics Estimated Time 1. Installation & Setup Downloading Cursor AI, configuring Java SDK, workspace preferences 5 min 2. Core AI Features Code completion, inline documentation, refactoring suggestions 8 min 3. Prompt Engineering Wr

📖 Read the Full Tutorial

🔗 Cursor AI IDE tutorial for Java developers complete guide 2026 — Full Guide with Code Examples

The full article includes:

✅ Step-by-step code examples (copy-paste ready)
✅ Complete working project (Spring Boot / Java)
✅ Common mistakes + fixes
✅ Production tips and benchmarks
✅ FAQ section

Published on How to Start Programming — practical AI and Java tutorials for developers.

How to Use GitHub Copilot in IntelliJ IDEA: Complete Guide 2026

Rajesh Mishra — Thu, 20 Aug 2026 08:11:48 +0000

This is a summary of the full tutorial published on howtostartprogramming.in.

TL;DR Get GitHub Copilot up and running in IntelliJ IDEA in five minutes: install the plugin, sign in with your GitHub account, turn on suggestions, tweak shortcuts, and let AI boost your coding speed. Step What to do Result 1⃣ Install Open Plugins → Search “GitHub Copilot” → Install → Restart IDE. Copilot plugin added to IntelliJ. 2⃣ Sign in Go to File → Settings → Tools → GitHub Copilot → Click Sign in → Authorize with your GitHub account. IDE is linked to your Copilot subscription. 3⃣ Enable In the same settings pane, toggle Enable Copilot and choose Inline suggestions or Popup completions . AI suggestions appear as you type. 4⃣ Customize shortcuts Open Keymap → Search “Copilot” → Assign keys (e.g., Ctrl+Alt+Space for Accept Suggestion , Ctrl+Shift+Space for Show Next ). Fast, keyboard‑

📖 Read the Full Tutorial

🔗 How to use GitHub Copilot in IntelliJ IDEA complete guide 2026 — Full Guide with Code Examples

The full article includes:

✅ Step-by-step code examples (copy-paste ready)
✅ Complete working project (Spring Boot / Java)
✅ Common mistakes + fixes
✅ Production tips and benchmarks
✅ FAQ section

Published on How to Start Programming — practical AI and Java tutorials for developers.

Spring Security OAuth2 login with Google and GitHub example — Complete Guide

Rajesh Mishra — Wed, 19 Aug 2026 07:18:49 +0000

Spring Security OAuth2 login with Google and GitHub example — Complete Guide

A practical, in-depth guide to Spring Security OAuth2 login with Google and GitHub example with examples.

INTRO

Every time a new micro‑service or web app goes live, the first thing users ask for is a quick, frictionless way to sign in. Throwing together a home‑grown username/password system feels safe, but it instantly becomes a maintenance nightmare—password resets, credential leaks, and compliance headaches pile up. The real problem isn’t authentication itself; it’s the overhead of managing identities that you don’t own.

OAuth2 providers like Google and GitHub already handle the heavy lifting: they store passwords, enforce MFA, and keep security patches up to date. Spring Security makes it possible to delegate authentication to these providers with just a few lines of configuration. Yet many developers stumble over the exact steps—registering the app, wiring the ClientRegistration, handling the callback, and persisting the principal. The result is a half‑baked login flow that either breaks on refresh or leaks user data.

The guide linked below walks through a production‑ready setup from scratch. It shows how to let users pick Google or GitHub, how to map the provider’s user attributes onto your domain model, and how to keep the configuration clean and testable. If you’ve ever fought with spring-security-oauth2-client or tried to patch together a custom filter, this article will save you hours of debugging.

WHAT YOU'LL LEARN

How to register OAuth2 clients on Google Cloud Console and GitHub Developer Settings and retrieve the necessary client IDs and secrets.
The minimal Spring Boot configuration (application.yml, SecurityFilterChain) that enables both providers without code duplication.
Mapping provider‑specific user attributes (email, avatar, login) to a unified OAuth2User implementation.
Persisting or provisioning a local User entity the first time a social login occurs, using Spring Data JPA.
Securing the callback endpoint, handling error scenarios, and customizing the post‑login redirect.
Tips for testing the OAuth2 flow locally (using ngrok, mock providers, and Spring’s @WebMvcTest).

A SHORT CODE SNIPPET

@Configuration
@EnableWebSecurity
public class SecurityConfig {

@Bean
SecurityFilterChain filterChain(HttpSecurity http) throws Exception {
http
.authorizeHttpRequests(auth -> auth
.requestMatchers("/", "/login**", "/error").permitAll()
.anyRequest().authenticated())
.oauth2Login(oauth -> oauth
.loginPage("/login")
.userInfoEndpoint(info -> info
.userService(customOAuth2UserService())));
return http.build();
}

@Bean
public OAuth2UserService<OAuth2UserRequest, OAuth2User> customOAuth2UserService() {
return new CustomOAuth2UserService(); // maps Google/GitHub attrs to our UserDetails
}
}

The snippet shows the core of the configuration: a SecurityFilterChain that opens the login page, enables OAuth2 for any provider defined in application.yml, and plugs in a custom OAuth2UserService to normalize the user data.

KEY TAKEAWAYS

Delegate, don’t duplicate – Let Google and GitHub handle authentication; your app only needs to translate the returned profile into a domain object.
Centralize provider configuration – Keep client IDs, secrets, and scopes in application.yml under spring.security.oauth2.client.registration to avoid hard‑coding values.
Normalize user attributes early – A single OAuth2User implementation prevents scattered if (provider.equals("github")) checks throughout the codebase.
Plan for the first‑login flow – Automatically create or link a local user record the first time a social account signs in, and store the provider key for future logins.

👉 Read the complete guide with step-by-step examples, common mistakes, and production tips:

Spring Security OAuth2 login with Google and GitHub example — Complete Guide

GitHub Copilot vs Cursor vs Windsurf: The Best AI Coding Tool of 2026

Rajesh Mishra — Tue, 18 Aug 2026 08:09:24 +0000

This is a summary of the full tutorial published on howtostartprogramming.in.

TL;DR: Which AI Coding Assistant Reigns Supreme in 2026? Overall Winner: Cursor – best blend of code‑completion accuracy, UI ergonomics, and extensibility for most developers. Key Strengths at a Glance Tool Accuracy & Speed IDE Integration Customization & Extensibility Pricing (2026) Best‑Fit Persona Cursor 🟢 94% pass‑rate on real‑world snippets; sub‑50 ms latency Native desktop app + VS Code, JetBrains, Neovim plugins Open‑source model hub, custom prompts, community “skill packs” Free tier (2 k tokens/mo); Pro $12/mo, Enterprise $45/mo Full‑stack devs, freelancers, teams needing rapid prototyping GitHub Copilot 🟡 89% pass‑rate; occasional “hallucinations” on niche APIs Deeply embedded in GitHub ecosystem; VS Code, JetBrains, Neovim Limited prompt tweaking; relies on Microsoft’s closed mod

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🔗 GitHub Copilot vs Cursor vs Windsurf best AI coding tool 2026 — Full Guide with Code Examples

The full article includes:

✅ Step-by-step code examples (copy-paste ready)
✅ Complete working project (Spring Boot / Java)
✅ Common mistakes + fixes
✅ Production tips and benchmarks
✅ FAQ section

Published on How to Start Programming — practical AI and Java tutorials for developers.