Java 的未来：2026 年及以后展望 The Future of Java: What to Expect in 2026 and Beyond

1. Introduction: Java’s Evolutionary Trajectory 引言：Java的演进轨迹

As we approach 2026, Java stands at a fascinating inflection point. Rather than merely maintaining its position, the platform is experiencing significant innovation through projects like Valhalla, Panama, Amber, and the Vector API. These initiatives represent more than incremental improvements—they fundamentally reimagine how Java handles data, interoperates with native code, and expresses developer intent.
随着我们迈向 2026 年，Java 正处于一个引人入胜的转折点。该平台不仅仅维持现有地位，还通过 Valhalla、Panama、Amber 和 Vector API 等项目实现了显著创新。这些举措不仅仅代表渐进式改进，它们从根本上重塑了Java处理数据、与本机代码互操作以及表达开发者意图的方式。

The six-month release cadence introduced with Java 9 has accelerated innovation while maintaining stability. Java 21 adoption has reached 45% within months of launch, demonstrating that the community embraces new capabilities when they deliver tangible value. This article examines the theoretical foundations, architectural principles, and strategic implications of Java’s most significant upcoming enhancements.
Java 9引入的六个月发布节奏在保持稳定性的同时加速了创新。Java 21在发布数月内采用率已达到45%，这表明当新功能带来切实价值时，社区乐于接受。本文将探讨Java即将到来的最重要增强功能的理论基础、架构原理和战略意义。

2. Project Valhalla: Rethinking the Object Model 重新思考对象模型

2.1 The Memory Problem Java Must Solve Java 必须解决的内存问题

Java’s object model, elegantly simple since 1995, now faces a critical mismatch with modern hardware realities. When Java was conceived, memory fetch operations and arithmetic operations had roughly equivalent costs, but today memory fetches are 200 to 1,000 times more expensive than arithmetic operations. This fundamental shift in hardware economics makes Java’s pointer-heavy approach to data representation increasingly problematic.
自 1995 年以来，Java 的对象模型优雅简洁，如今却面临与现代硬件现实的严重不匹配。Java 诞生时，内存取指作和算术运算的成本大致相同，但如今内存取指作的成本是算术运算的 200 到 1000 倍。硬件经济学的这一根本转变使得 Java 以指针为主的数据表示方法变得越来越棘手。

Consider a simple data structure like coordinates or color values. Traditional Java creates full heap objects with identity and overhead for even the smallest data carriers. This indirection cascade—where an array of objects contains references that point to scattered heap locations—destroys cache locality and forces expensive memory traversals.
考虑一个简单的数据结构，比如坐标或颜色值。传统 Java 能够为最小的数据载体创建带有身份和开销的完整堆对象。这种间接级联——即一组对象包含指向散布堆位置的引用——破坏了缓存的局部性，并迫使昂贵的内存遍历。

2.2 Value Types: Codes Like a Class, Works Like an Int 值类型：像类一样编码，像int一样工作

Project Valhalla introduces value classes that combine object-oriented abstractions with primitive performance characteristics, allowing objects without identity that can have optimized encodings. The conceptual breakthrough lies in recognizing that not all objects need identity. Many data structures—coordinates, complex numbers, tuples—represent pure values rather than entities.
Project Valhalla 引入了将面向对象抽象与原始性能特性结合的值类，使无身份的对象能够获得优化的编码。概念上的突破在于认识到并非所有物体都需要身份。许多数据结构——坐标、复数、元组——表示纯值而非实体。

Value classes sacrifice identity-dependent features (reference equality via ==, synchronization) in exchange for dramatic memory and performance improvements. Value classes still support null since they are reference types, while primitive classes subject to stricter constraints give up null support entirely but enable even more aggressive optimizations.
值类牺牲了与身份相关的特征（通过==、同步实现参考等式），以换取显著的内存和性能提升。值类仍然支持空，因为它们是引用类型，而受更严格约束的原始类则完全放弃了空，但允许更激进的优化。

2.3 The Architectural Impact 架构影响

The implications extend far beyond individual objects. Early-access benchmarks from October 2025 show nearly 3x faster performance when summing years from a 50-million-element array of LocalDate instances, reducing average execution time from approximately 72 ms to 25 ms compared to identity-based objects.
其影响远不止于单个对象。2025 年 10 月的抢先访问基准显示，在对 5000 万元素 LocalDate 实例的数组中求和年份时，性能几乎快了 3 倍，相较于基于身份标识的对象，平均执行时间从约 72 毫秒缩短到 25 毫秒。

This performance gain emerges from flattening—embedding value object data directly in arrays and fields rather than storing references. Instead of an array containing pointers to scattered heap objects, you get a contiguous block of actual data, perfectly aligned for modern CPU cache architectures.
这种性能提升来自于扁平化——将值对象数据直接嵌入数组和字段，而不是存储引用。你得到的不是包含指向散布堆对象的指针的数组，而是连续的实际数据块，完美适配现代CPU缓存架构。

2.4 Enhanced Generics and Reification 增强泛型与具体化

Valhalla’s scope includes addressing Java’s long-standing generic type erasure limitation. Enhanced generics aim to enable generic types for object references, primitives, value types, and potentially void, removing the need for boxing workarounds. This means List<int> becomes possible without wrapper objects, eliminating both memory overhead and allocation pressure.
Valhalla 的范围包括解决 Java 长期存在的通用类型擦除限制问题。增强型泛型旨在支持对象引用、原语、值类型，甚至可能的 void 泛型，从而消除了对盒装变通方法的需求。这意味着 List<int> 无需包装对象即可实现，消除了内存开销和分配压力。

2.5 Timeline and Current Status 时间线与现状

As of October 2025, JEP 401: Value Classes and Objects has early-access builds implementing value classes with preview features available in early-access builds of JDK 26. The anticipated delivery spans multiple releases through a steady stream of enhancements rather than a single monolithic update. Realistic stabilization targets point toward Java 26-27 (2026-2027) for production readiness.
截至 2025 年 10 月，JEP 401：值类与对象包含早期访问版本，实现了带有预览功能的值类，这些版本可在 JDK 26 的早期体验版本中提供。预期的发布是通过持续不断的增强，跨越多个版本，而非单一的单一更新。现实的稳定目标指向 Java 26-27（2026-2027）以实现生产准备。

3. Project Panama: Bridging Java and Native Code 连接Java与原生代码(本机代码)

3.1 The JNI Problem Statement JNI 问题陈述

For decades, the Java Native Interface served as Java’s gateway to native libraries, but its complexity imposed significant costs. JNI demands expertise in both Java and native programming, often leading to error-prone glue code with performance overhead from frequent crossing boundaries, manual memory management risking leaks or crashes, and safety concerns from direct memory access.
几十年来，Java 原生接口一直是 Java 访问本地库的入口，但其复杂性带来了巨大的成本。JNI 要求同时具备 Java 和原生编程的专业知识，常常导致易出错的胶水代码，频繁跨越边界带来性能开销，手动内存管理可能导致泄漏或崩溃，以及直接访问内存带来的安全隐患。

3.2 Foreign Function & Memory API Architecture 外部函数与内存 API 架构

Project Panama’s Foreign Function and Memory API became standard in Java 22 after incubation since Java 14, providing developers a direct way to call native functions, allocate native memory, and map native data structures. The architectural elegance lies in type-safe memory access without sacrificing performance.
Project Panama 的外部函数与内存 API 自 Java 14 孵化后成为 Java 22 的标准，为开发者提供了直接调用本地函数、分配本地内存和映射本地数据结构的方式。架构上的优雅在于类型安全内存访问，同时不牺牲性能。

The API introduces several key abstractions:
该 API 引入了几个关键抽象：

Memory Segments : Bounded, temporal, thread-confined views over memory sources (on-heap or off-heap). Unlike raw pointers, segments carry size information and lifecycle management.
内存段 ：对内存源（堆上或堆外）的有界、时间性、线程限制视图。与原始指针不同，分段携带大小信息和生命周期管理。

Linker : A bridge between the JVM and C/C++ native code (C ABI), with platform-specific implementations for Win64, SysVx64, LinuxAArch64, and MacOsAArch64.
链接器 ：连接 JVM 与 C/C++ 原生代码（C ABI）之间的桥梁，支持针对 Win64、SysVx64、LinuxAArch64 和 MacOsAArch64 的平台特定实现。

Function Descriptors : Type-safe specifications of native function signatures, ensuring proper marshalling between Java and native conventions.
函数描述符 ：原生函数签名的类型安全规范，确保 Java 与本地约定之间的正确编组。

Arena-Based Memory Management : Scoped allocation that automatically releases resources, preventing the memory leaks that plague manual JNI code.
基于 Arena 的内存管理 ：有范围的分配，自动释放资源，防止困扰手动 JNI 代码的内存泄漏。

3.3 Performance and Safety Characteristics 性能与安全特性

The trade-off between safety and raw performance deserves examination. While interop code is written in Java, it cannot be considered 100% safe since the runtime must trust developer descriptions of native functions, which is why access to the foreign linker is a restricted operation requiring the foreign.restricted=permit flag.
安全性与纯性能之间的权衡值得深入探讨。虽然互作代码用 Java 编写，但不能被视为百分之百安全，因为运行时必须信任开发者对本地函数的描述，这也是访问外部链接器是受限作的原因，需要使用 foreign.restricted=permit 标志。

This design intentionally surfaces the inherent risks of native interop while providing guardrails against common errors. The API prevents many categories of bugs—buffer overruns, use-after-free, null pointer dereferences—through compile-time and runtime checks, yet acknowledges that native code boundaries represent trust boundaries.
这种设计有意暴露了本地互操作的内在风险，同时为常见错误提供防护措施。该 API 通过编译时和运行时检查防止了许多类型的错误——缓冲区超载、释放后使用、空指针去引用——同时承认本地代码边界代表信任边界。

3.4 Production Status 生产状态

As of 2025, the FFM API is considered largely stable after rigorous refinement since Java 19, with streamlined memory management, enhanced safety measures, and customization features. The transition from preview to production in Java 22 marks a significant milestone, positioning Panama as JNI’s modern replacement for new development.
截至 2025 年，经过自 Java 19 以来严格优化的 FFM API 基本稳定，具备简化的内存管理、增强的安全措施和自定义功能。Java 22 从预览到生产的转变标志着一个重要里程碑，使Panama成为 JNI 新开发的现代替代品。

4. Project Amber: The Evolution of Expression 表达能力的演进

4.1 The Ceremony Reduction Philosophy 仪式简化理念

Project Amber’s mission is identifying and incubating smaller, productivity-oriented language features that make everyday Java code more readable, writable, and maintainable through a process often called right-sizing language ceremony. Unlike projects targeting performance or interoperability, Amber focuses on developer ergonomics and expressiveness.
Project Amber 的使命是识别并孵化更小的、以生产力为导向的语言特性，使日常 Java 代码更易读、更易写和更易维护，这一过程通常被称为“语言仪式感适度化”。与注重性能或互作性的项目不同，Amber 专注于开发者的人体工学和表现力。

4.2 Completed Transformations 已完成的功能

The delivered features have fundamentally altered how modern Java code looks and feels:
这些已交付的功能从根本上改变了现代 Java 代码的界面和体验：

Local Variable Type Inference (var) : Eliminates redundant type declarations where the compiler can infer types, reducing noise without sacrificing type safety.
局部变量类型推理（var） ： 消除编译器可能推断类型的冗余类型声明，减少噪声而不牺牲类型安全。

Switch Expressions : Transformed switch from a statement to an expression with exhaustiveness checking and pattern matching capabilities, enabling concise, safe conditional logic.
Switch表达式 ：将从语句转换为具备穷尽性检查和模式匹配功能的表达式，实现简洁安全的条件逻辑。

Text Blocks : Multi-line string literals that respect formatting, eliminating concatenation gymnastics for SQL, JSON, and HTML.
文本块 ：多行字符串文字，尊重格式，消除了 SQL、JSON 和 HTML 的串接繁琐。

Records : Compact syntax for immutable data carriers with automatically derived equality, hashing, and toString implementations.
记录类 ：为不可变数据载体提供紧凑语法，支持自动推导的等式、哈希和 toString 实现。

Sealed Classes : Control over inheritance hierarchies by explicitly permitting which types can extend or implement a sealed type, enabling exhaustive pattern matching.
密封类 ：通过明确允许哪些类型可以扩展或实现密封类型，控制继承层级，实现穷尽模式匹配。

Pattern Matching : Enhanced instanceof and switch to allow pattern matching, eliminating explicit casting after type checks and enabling sophisticated data deconstruction.
模式匹配 ：增强实例和切换支持模式匹配，消除类型检查后的显式铸造，实现复杂的数据解构。

4.3 Currently Evolving Features 当前演进中的功能

For 2025, Amber focuses on finalizing four preview features: Flexible Constructor Bodies allowing code before super/this calls, Compact Source Files and Instance Main Methods simplifying entry points, Module Import Declarations for concise package imports, and Primitive Patterns for matching on primitive types.
2025 年，Amber 专注于完善四个预览功能：灵活构造体支持在 super/this 调用前编写代码，简化入口点的紧凑源文件 Compact Source Files 和实例主方法，用于简洁包导入的模块导入声明，以及用于匹配原始类型的原始模式 Primitive Patterns。

Beyond these, exploratory work continues on:
除此之外，探索性工作仍在继续：

Custom Deconstructors : Extending pattern matching beyond records to arbitrary classes, enabling deconstruction without requiring record constraints.
自定义解构器 ：将模式匹配扩展到任意类别，实现拆解而无需记录约束。

Withers : A with expression that deconstructs an instance into variables, allows reassigning their values, then calls a constructor to produce a modified copy.
Withers ：一个表达式，将实例拆解为变量，允许重新分配其值，然后调用构造函数生成修改后的副本。

String Templates : Mechanisms for safe, efficient string interpolation that disappeared from Java 23 for redesign but remains under active development.
字符串模板 ：用于安全高效字符串插值的机制，曾在 Java 23 中因重新设计而消失，但仍在积极开发中。

4.4 The Data-Oriented Programming Paradigm 面向数据编程范式

Amber’s development efforts align closely with Data-Oriented Programming, focusing on making data immutable, separating data from behavior, and designing data aggregates with clear, predictable structures. This represents a complementary approach to traditional object-oriented programming rather than replacement, providing tools for scenarios where transparent data modeling offers advantages over encapsulation.
Amber 的开发工作与面向数据编程高度契合，专注于使数据不可变、将数据与行为分离，并设计具有清晰、可预测结构的数据聚合。这代表了传统面向对象编程的互补方法，而非替代，为透明数据建模相较封装更有利的场景提供了工具。

5. Vector API: Explicit SIMD Programming 向量(Vector) API：显式 SIMD 编程

5.1 The Auto-Vectorization Limitation 自动向量化的局限性

Modern CPUs offer SIMD (Single Instruction, Multiple Data) capabilities that can perform operations on multiple data elements simultaneously. Today, developers writing scalar operations that should be vectorized need to understand HotSpot’s auto-vectorization algorithm and its limitations to achieve reliable performance, and in some cases it may not be possible to write transformable scalar operations.
现代 CPU 提供 SIMD（单指令，多数据）功能，可以同时对多个数据元素执行作。如今，编写应被矢量化的标量运算的开发者需要理解 HotSpot 的自动向量化算法及其局限性，以实现可靠性能，在某些情况下可能无法编写可变换的标量运算。

This reliance on compiler heuristics makes performance unpredictable. Simple changes that seem semantically identical can prevent vectorization, leaving developers with no reliable way to express vectorizable intent.
这种对编译器启发式的依赖使得性能变得不可预测。看似语义相同的简单更改可能阻止矢量化，使开发者无法可靠地表达可矢量化的意图。

5.2 Vector API Design Principles Vector API设计原则

The Vector API provides vector types, operations, and factories for performing SIMD operations directly in Java, with clear and concise API capable of expressing a wide range of vector computations generic with respect to vector size, enabling portability across hardware supporting different vector sizes.
Vector API 提供了向量类型、作和工厂，用于直接在 Java 中执行 SIMD 作，API 清晰简洁，能够表达关于向量大小的多种通用向量计算，实现跨硬件的可移植性，支持不同向量大小。

The architectural approach prioritizes:
架构方法优先考虑：

Platform Agnosticism : Code written using Vector API runs on x64 (SSE, AVX), ARM (NEON, SVE), and RISC-V platforms with appropriate specialization.
平台无关性：使用Vector API 编写的代码可在 x64（SSE、AVX）、ARM（NEON、SVE）和 RISC-V 平台上运行，并具备相应的专业化。

Predictable Compilation : On capable x64 architectures, HotSpot C2 should compile vector operations to corresponding efficient vector instructions with developer confidence that expressed operations map closely to relevant vector instructions.
可预测编译 ：在具备功能 x64 架构的条件下，HotSpot C2 应能以开发者信心将向量运算编译为对应高效的向量指令，且表达作与相关向量指令高度匹配。

Graceful Degradation : When vector computation cannot be fully expressed as vector instructions, perhaps because the architecture doesn’t support required instructions, the implementation degrades gracefully and still functions.
优雅降级 ：当向量计算无法完全用向量指令表达时，可能因为架构不支持必需指令，实现会优雅地退化但仍能正常运行。

5.3 Performance Characteristics 性能特征

Benchmarks show simplified cases of summing two large integer arrays achieving over 4x faster performance using the Vector API compared to scalar operations. Real-world gains depend heavily on data access patterns, cache behavior, and the specific operations involved.
基准测试展示了简化的两个大型整数组求和案例，使用Vector API 实现了标量运算速度超过 4 倍的性能。实际的收益高度依赖于数据访问模式、缓存行为以及具体作。

The performance story includes important caveats. Main memory accesses cost 60–100+ CPU cycles per access, so as arrays grow beyond CPU cache sizes, more memory accesses reduce Vector API benefits. Additionally, JIT auto-vectorization sometimes achieves similar results for simple patterns, making the API most valuable for complex algorithms that defeat auto-vectorization.
表演故事包含重要的警告。主存访问每次访问消耗 60–100+ CPU 周期，因此随着数组超过 CPU 缓存容量，更多内存访问会降低向量 API 的优势。此外，JIT 自动向量化有时也能在简单模式中取得类似效果，使得该 API 对于击败自动向量化的复杂算法尤为有价值。

5.4 Integration with Panama and Valhalla 与Panama和Valhalla的集成

The Vector API leverages Intel Short Vector Math Library on x64 and SIMD Library for Evaluating Elementary Functions on ARM and RISC-V, linking to native mathematical functions using Panama’s Foreign Function & Memory API. Furthermore, the Vector API uses box types as proxies for primitive types, forced by current generic limitations, with expected changes when Valhalla introduces more capable generics.
向量 API 利用了基于 x64 的 Intel Short Vector Math Library 和在 ARM 和 RISC-V 上计算初等函数的 SIMD 库，并通过 Panama 的 Foreign Function & Memory API 链接到本地数学函数。此外，Vector API 使用盒子类型作为原始类型的代理，这是受当前通用限制所限，预计当Valhalla推出更强大的通用类型时会发生变化。

5.5 Current Status and Timeline 现状与时间线

JEP 529: Vector API (Eleventh Incubator) targeted JDK 26 in December 2025, indicating continued refinement before finalization. The extended incubation reflects the complexity of achieving consistent performance across diverse hardware platforms while maintaining API stability. Realistic stabilization likely arrives with Java 26 (2026).
JEP 529：Vector API（第十一孵化器）于 2025 年 12 月针对 JDK 26，表明在最终确定前还在持续完善。延长的孵化反映了在不同硬件平台上实现稳定性能的复杂性，同时保持 API 稳定性。现实稳定很可能会在 Java 26（2026 年）中实现。

6. Module System: Adoption and Reality 模块系统：采纳与现实

6.1 JPMS Conceptual Foundations JPMS 概念基础

The Java Platform Module System is a code-level structure that doesn’t change JAR packaging but adds a higher-level descriptor through the module-info.java file, making it easier for developers to organize large applications and libraries while improving platform structure and security.
Java 平台模块系统是一种代码级结构，不改变 JAR 封装，但通过 module-info.java 文件添加更高级的描述符，使开发者更容易组织大型应用和库，同时提升平台结构和安全性。

The module system addresses several architectural problems:
模块系统解决了若干架构问题：

Classpath Hell : The classpath ultimately becomes a large, undifferentiated bucket into which all dependencies are inserted, with the module path adding a level above that acts as storage for packages while choosing which ones are accessible.
类路径地狱 ：类路径最终变成一个大型、未区分的桶，所有依赖都插入其中，模块路径在上方增加了一层，作为包的存储，同时选择哪些包是可访问的。

Encapsulation : Modules explicitly declare which packages they export and which other modules they require, preventing accidental dependencies on internal APIs.
封装 ：模块明确声明它们导出哪些包以及需要哪些其他模块，防止对内部 API 的意外依赖。

Explicit Dependencies : Compile-time verification of module dependencies reduces runtime surprises and facilitates static analysis.
显式依赖 ：编译时验证模块依赖，减少运行时的意外，便于静态分析。

6.2 Adoption Patterns and Challenges 采用模式与挑战

As of 2025, JPMS usage has grown in GraalVM native image compilation, where modular applications enable ahead-of-time optimization by excluding unused code paths, resulting in compact executables suitable for serverless and edge scenarios.
截至 2025 年，JPMS 在 GraalVM 原生图像编译中的应用有所增长，模块化应用通过排除未使用的代码路径实现提前优化，从而生成适合无服务器和边缘场景的紧凑可执行文件。

However, enterprise adoption shows a measured pace. Spring Boot has progressed toward JPMS integration, offering partial support for modular JARs in version 3 and full modularization of auto-configuration in Spring Boot 4, splitting large artifacts into targeted modules to minimize classpath pollution.
然而，企业的采纳速度显示出稳健的步伐。Spring Boot 已逐步实现 JPMS 集成，版本 3 部分支持模块化 JARs，Spring Boot 4 实现了自动配置的全面模块化，将大型伪造拆分为目标模块以减少类路径污染。

The gradual adoption reflects practical constraints. Many organizations maintain substantial legacy codebases where modularization represents significant refactoring investment. The automatic module mechanism—where non-modular JARs receive implicit module descriptors—provides a migration path but doesn’t deliver full benefits.
逐步采用反映了实际的限制。许多组织维护着庞大的遗留代码库，模块化需要大量重构投资。自动模块机制——非模块化 JAR 接收隐式模块描述符——提供了迁移路径，但未能带来全部优势。

6.3 Strong Encapsulation Evolution 强封装的演进

From Java 16 onward, strong encapsulation became the default, turning illegal accesses into errors unless explicitly allowed via flags, with Java 17 making the –illegal-access option obsolete and enforcing strict encapsulation. This progression balanced migration compatibility with security goals.
从 Java 16 起，强封装成为默认，除非通过标志明确允许，否则非法访问会变成错误，Java 17 使 –illegal-access 选项变得过时，并强制严格封装。这一进展平衡了迁移兼容性与安全目标。

The enforcement timeline demonstrates Java’s philosophy: provide warnings and migration paths, then strengthen guarantees once the community adapts. Libraries and frameworks that relied on internal JDK APIs faced breaking changes, but the extended timeline allowed orderly transitions.
执法时间表体现了 Java 的理念：先提供警告和迁移路径，社区适应后再加强保障。依赖内部 JDK API 的库和框架面临重大变更，但延长的时间线允许有序过渡。

6.4 Future of Modular Java 模块化 Java 的未来

Enterprise adoption aligns with rising Java 21 use, with surveys showing 43% of developers leveraging it in Jakarta EE contexts, indicating broader integration of modular practices for maintainable, secure systems.
企业采用率与 Java 21 使用率的上升相符，调查显示 43%的开发者在雅加达 EE 环境中利用了它，表明模块化实践的更广泛整合，以实现可维护且安全的系统。

The module system’s future likely involves deeper tooling integration, improved IDE support, and clearer best practices. Java 25’s JEP 511 introduced module import declarations via import module M; syntax, allowing package-level imports of all public types from exported packages to simplify usage, showing continued evolution toward developer-friendly module interaction.
模块系统的未来可能涉及更深层的工具集成、改进 IDE 支持以及更清晰的最佳实践。Java 25 的 JEP 511 引入了通过 import 模块 M 实现模块导入声明;该语法允许从导出包导入所有公共类型，简化使用，显示出向开发者友好模块交互的持续演进。

7. Community Governance and the OpenJDK Process 社区治理与 OpenJDK 进程

7.1 The JCP and JEP Relationship JCP 与 JEP 的关系

The JEP process does not supplant the Java Community Process, as the JCP remains the governing body for all standard Java SE APIs and related interfaces, with accepted proposals requiring parallel efforts in the JCP through JSRs for standard interface changes.
JEP 流程并未取代 Java 社区进程，因为 JCP 仍然是所有标准 Java SE API 及相关接口的管理机构，而被接受的提案则需要通过 JSR 在 JCP 中进行并行的标准接口变更工作。

This dual-track system balances innovation and standardization:
这一双轨体系平衡了创新与标准化：

JEP (JDK Enhancement Proposal) : Allows OpenJDK committers to work more informally before becoming formal Java Specification Requests, serving as long-term roadmaps for JDK Release Projects.
JEP（JDK 增强提案） ： 允许 OpenJDK 提交者在成为正式 Java 规范请求之前更为非正式地工作，作为 JDK 发布项目的长期路线图。

JSR (Java Specification Request) : Formal proposals defining specifications that all Java implementations must follow, ensuring consistency across vendors.
JSR（Java 规范请求） ： 正式提案，定义所有 Java 实现必须遵循的规范，确保各厂商间的一致性。

7.2 Decision-Making Structure 决策结构

The OpenJDK Lead ultimately decides which JEPs to accept for inclusion into the Roadmap but relies on demonstrated expertise of Reviewers, Group Leads, and Area Leads when evaluating incoming proposals. This hierarchy acknowledges that no single person can maintain expert-level understanding across Java’s vast complexity.
OpenJDK 负责人最终决定哪些 JEP 被纳入路线图，但在评估新提案时，依赖评审员、组长和区域负责人的专业能力。这一层级体系承认，没有单一个人能够在 Java 庞大的复杂性中保持专家级的理解。

Successful JEPs require building consensus through reviewer endorsements and group/area lead support. Endorsement by a Group or Area Lead is meant to be a reasonably strong statement equivalent to “I will argue that this JEP should be funded”.
成功的 JEP 需要通过评审推荐和组/区域负责人支持来建立共识。由团体或区域负责人背书应当是一种相当有力的声明，类似于“我将主张该 JEP 应获得资金支持”。

7.3 The Six-Month Release Cadence Impact 六个月发布节奏影响

JDK 25 reached General Availability on 16 September 2025, with features and schedule tracked via the JEP Process as amended by the JEP 2.0 proposal. The predictable cadence fundamentally changed Java’s innovation model.
JDK 25 于 2025 年 9 月 16 日正式上市，功能和进度通过 JEP 流程（经 JEP 2.0 提案修订）进行跟踪。这种可预测的节奏从根本上改变了 Java 的创新模式。

Previous multi-year release cycles created pressure to include immature features to avoid missing release windows. The six-month model allows features to mature through multiple preview rounds across releases without blocking other improvements. This patience-enabling structure proves crucial for complex initiatives like Valhalla, which require extensive real-world testing before stabilization.
此前多年发布周期带来了压力，必须包含尚未成熟的功能，以避免错过发布窗口。六个月模式允许功能通过多次预览轮次在不同版本中成熟，而不阻碍其他改进。这种耐心驱动的结构对于像瓦尔哈拉这样需要大量真实测试才能稳定的复杂项目至关重要。

7.4 Community Participation 社区参与

The Java Community Process was initially formalized in December 1998, with much of Java’s success attributed to how the language evolves and how the worldwide community collaborates in that evolution. Today’s participation mechanisms include mailing lists, early-access builds, and public issue tracking.
Java 社区进程最初于 1998 年 12 月正式确立，Java 的成功很大程度上归功于语言的发展以及全球社区在这一演变中的协作。如今的参与机制包括邮件列表、抢先体验版本和公共议题跟踪。

The transparency requirements have evolved. JSR Expert Groups must hold discussions on public mailing lists, use public issue-tracking mechanisms to record progress, and publish working documents for all to see. This openness contrasts with earlier, more closed development models.
透明度要求已经演变。JSR 专家组必须在公开邮件列表上进行讨论，利用公开问题跟踪机制记录进展，并发布工作文件供所有人查看。这种开放性与早期更封闭的发展模式形成鲜明对比。

8. Java’s Competitive Positioning Java的竞争定位

8.1 The Multi-Paradigm Landscape 多范式格局

Java faces competition on multiple fronts, each representing different trade-offs:
Java 面临多方面的竞争，每一个领域都带来了不同的权衡：

Kotlin : Kotlin has gained considerable momentum, particularly after Google declared it the preferred language for Android development in 2017, though Java remains far more popular with 33.27% vs 9.16% in Stack Overflow’s 2022 survey. Kotlin’s appeal lies in interoperability—it runs on the JVM and integrates seamlessly with existing Java code, enabling gradual adoption rather than wholesale rewrites.
Kotlin ：Kotlin 获得了相当大的势头，尤其是在谷歌在 2017 年宣布其为 Android 开发首选语言之后，尽管 Java 在 Stack Overflow 2022 年调查中仍更受欢迎，达到 33.27%对 9.16%。Kotlin 的吸引力在于互作性——它运行在 JVM 上，并与现有 Java 代码无缝集成，实现渐进式采用，而非全面重写。

Go : Designed for simplicity and concurrency, Go targets microservices and cloud infrastructure where fast compilation and straightforward deployment matter more than rich ecosystems. Go’s garbage collection and lack of generics (until recently) represent intentional trade-offs favoring simplicity.
Go ：Go 设计为简洁和并发，面向微服务和云基础设施，在这些领域，快速编译和直接部署比丰富的生态系统更重要。Go 的垃圾收集和直到最近缺乏通用药，都是为了简化而有意做出的权衡。

Rust : By 2025, Rust has established itself as the language of choice for systems programming, WebAssembly, and performance-critical applications, thanks to emphasis on memory safety and zero-cost abstractions. Rust’s steep learning curve and compile-time strictness target scenarios where safety and performance justify complexity.
Rust ：到 2025 年，Rust 已成为系统编程、WebAssembly 及性能关键应用的首选语言，得益于对内存安全和零成本抽象的重视。Rust 陡峭的学习曲线和编译时的严格性，针对的是安全性和性能合理化复杂性场景。

8.2 Java’s Enduring Strengths Java的持久优势

As of 2025, Java continues to hold around 15% to 16% of the programming language market, with 68% of applications running on Java or the JVM, and 99% of organizations actively using Java. Several factors sustain this position:
截至 2025 年，Java 仍占据约 15%至 16%的编程语言市场份额，68%的应用程序运行在 Java 或 JVM 上，99%的组织积极使用 Java。支持这一立场的因素有以下几点：

Ecosystem Maturity : Decades of library development, framework evolution, and tooling refinement create network effects difficult to replicate. Spring, Jakarta EE, testing frameworks, build tools, profilers—the complete development stack exists and works well.
生态系统成熟度 ：数十年的库开发、框架演进和工具优化，造成了难以复制的网络效应。Spring、Jakarta EE、测试框架、构建工具、性能分析器——完整的开发栈都存在且运行良好。

Enterprise Stability : Frameworks and libraries are moving to support or require newer Java versions, with Java 17 emerging as a new baseline since Spring, JUnit, Gradle 9, and upcoming Maven 4 require Java 17 or higher. This coordinated evolution maintains ecosystem coherence while advancing capabilities.
企业稳定性 ：框架和库正在支持或要求更新的 Java 版本，Java 17 作为新的基线，自 Spring 以来，JUnit、Gradle 9 以及即将推出的 Maven 4 都要求 Java 17 或更高版本。这种协调进化在提升能力的同时，维持了生态系统的连贯性。

Performance Evolution : Java’s performance continues improving through JIT advancements, garbage collector innovations (ZGC, Shenandoah), and now the Project Valhalla and Vector API initiatives. The performance gap with lower-level languages narrows for many workloads.
性能演进 ：Java 的性能通过 JIT 的进步、垃圾回收器创新（ZGC、Shenandoah）以及现在的 Project Valhalla 和 Vector API 项目持续提升。低级别语言的性能差距在许多工作负载下会缩小。

Cloud Native Adaptation : Interoperability between languages enables developers to integrate Rust’s high-performance components into existing Java programs, with 15% of developers using Java together with their Rust projects. This polyglot approach allows leveraging each language’s strengths rather than forcing all-or-nothing choices.
云原生适应 ：语言间的互作性使开发者能够将 Rust 的高性能组件集成到现有的 Java 程序中，15% 的开发者将 Java 与他们的 Rust 项目一起使用。这种多语种方法允许利用每种语言的优势，而非强制选择全有或全无。

8.3 The AI and Machine Learning Context 人工智能与机器学习背景

New frameworks like Embabel, Koog, Spring AI, and LangChain4j drive rapid adoption of AI-native and AI-assisted development in Java. While Python dominates machine learning research and experimentation, Java’s role in production deployment—where reliability, monitoring, and integration with existing systems matter—remains substantial.
像 Embabel、Koog、Spring AI 和 LangChain4j 这样的新框架推动了 Java 中 AI 原生和辅助开发的快速采用。虽然 Python 主导了机器学习的研究和实验，但 Java 在生产部署中的作用依然重要——在生产环境中，可靠性、监控以及与现有系统的集成至关重要。

8.4 Threat Assessment 威胁评估

The greatest challenge isn’t displacement by a single competitor but fragmentation across specialized niches. Different languages optimize for different constraints:
最大的挑战不是被单一竞争者取代，而是在专业细分市场中的碎片化。不同语言针对不同约束进行优化：

• Development Speed : Ruby, Python remain faster for MVPs and startups racing toward product-market fit
  开发速度 ：Ruby 和 Python 依然更快，对于 MVP 和初创企业，正朝着产品市场契合争取
• Native Performance : Rust, C++ maintain advantages for systems programming and embedded contexts
  原生性能 ：Rust、C++ 在系统编程和嵌入式环境中保持优势
• Simplicity : Go’s minimalism appeals to teams prioritizing maintainability over expressiveness
  简洁性 ：Go 的极简主义适合优先考虑可维护性而非表现力的团队
• Mobile : Swift (iOS) and Kotlin (Android) offer superior native platform integration
  移动端 ：Swift（iOS）和 Kotlin（Android）提供了更优的原生平台集成

Java’s strategy appears to be expanding its range rather than defending a single niche. Valhalla targets performance-critical scenarios, Panama enables systems-level integration, Amber improves developer productivity, and the Vector API addresses numerical computing. This multi-front evolution aims to keep Java relevant across the broadest possible spectrum of use cases.
Java的策略似乎是扩大其产品范围，而非守护单一细分市场。Valhalla 针对性能关键场景，Panama 实现系统级集成，Amber 提升开发者生产力，Vector API 专注于数值计算。这一多方面的演进旨在保持 Java 在最广泛的用例中保持相关性。

9. Conclusion: What We’ve Learned 结论：我们的收获

As we survey Java’s trajectory toward 2026 and beyond, several principles emerge:
展望Java走向2026年及以后的发展轨迹，出现了几个原则：

1. Performance Through Smarter Data Representation: Project Valhalla’s value types address a fundamental architectural mismatch between Java’s object model and modern hardware, with demonstrated 3x performance improvements that could reshape Java’s positioning in performance-sensitive domains.
   通过更智能的数据表示实现性能 ：Project Valhalla 的价值类型解决了 Java 对象模型与现代硬件之间的根本架构不匹配问题，展示了三倍的性能提升，可能重塑 Java 在性能敏感领域的定位。

2. Simplified Native Interoperability: Project Panama’s Foreign Function & Memory API eliminates JNI complexity while maintaining type safety, finally providing a modern mechanism for the native integration that enterprise systems regularly require.
   简化原生互作性 ：Project Panama 的外部函数与内存 API 消除了 JNI 的复杂性，同时保持类型安全，最终为企业系统日常所需的原生集成提供了现代化机制。

3. Expressive Power Without Ceremony: Project Amber’s continuous stream of enhancements—from pattern matching to records to sealed classes—demonstrates that productivity improvements need not compromise type safety or runtime performance.
   无需仪式感的表达力 ：Project Amber 持续不断的改进——从模式匹配到记录再到密封类——证明了生产力提升不必牺牲类型安全或运行时性能。

4. Explicit Parallelism: The Vector API provides developers direct access to SIMD capabilities with platform-agnostic abstractions, addressing performance-critical scenarios that auto-vectorization cannot reliably handle.
   显式并行性 ：向量 API 为开发者提供基于平台无关抽象的 SIMD 能力的直接访问，解决自动向量化无法可靠处理的性能关键场景。

5. Measured Module Adoption: While JPMS provides architectural benefits, practical adoption shows gradual progression driven by specific use cases (GraalVM native images, cloud-native applications) rather than wholesale migration pressure.
   模块的采用率：虽然 JPMS 在架构上有优势，但实际采用则由特定用例（如 GraalVM 原生映像、云原生应用）推动，而非大规模迁移压力。

6. Transparent Governance: The combination of JEP and JCP processes, accelerated by the six-month release cadence, enables rapid innovation while maintaining stability and community input.
   透明治理 ：JEP 与 JCP 流程的结合，通过六个月一次的发布周期加速，实现快速创新，同时保持稳定和社区参与。

7. Competitive Resilience Through Evolution: Java maintains relevance not by defending historical strengths but by expanding capabilities into adjacent domains, from low-level performance to modern language features to AI integration.
   通过演进保持竞争韧性：Java 保持相关性，不是靠捍卫历史优势，而是通过扩展能力到邻近领域，从低级性能到现代语言特性再到人工智能集成。

The Java platform entering 2026 represents something more interesting than merely maintaining legacy systems. Through careful attention to hardware realities, developer ergonomics, and ecosystem evolution, Java positions itself as a platform that can grow with changing requirements rather than one frozen in past successes. Whether this evolutionary approach successfully navigates the challenges ahead will depend on execution, community response, and the ability to deliver promised capabilities as stable, production-ready features rather than perpetual previews.
进入 2026 年的 Java 平台代表着比单纯维护遗留系统更有趣的事情。通过对硬件现实、开发者的人体工学和生态系统演进的细致关注，Java 定位为一个能够随着需求不断变化而成长的平台，而非停滞于过去的成功。这种进化式方法能否成功应对未来的挑战，取决于执行力、社区响应以及能否将承诺的功能作为稳定、适量生产功能而非永久预览交付。

The timeline ahead demands patience. Valhalla’s value types won’t reach production before 2026-2027. The Vector API continues incubating toward finalization. Yet this measured pace reflects a mature platform that values stability over rushing features to market. For organizations building systems meant to operate for decades, Java’s careful evolution and backward compatibility represent assets, not liabilities.
前方的时间线需要耐心等待。Valhalla的价值类型要到 2026-2027 年才会投入生产。Vector API 仍在潜伏，朝着最终成型迈进。然而，这种稳健的节奏反映了一个成熟的平台，重视稳定性而非仓促推出的功能。对于构建那些计划运行数十年的系统的组织来说，Java 的细致演进和向后兼容是资产，而非负担。