C++ in 2025: How the Language Is Adapting to a Shifting Tech Landscape
C++ adapts to modern challenges with upcoming C++26 features, AI-assisted development, and enhanced security measures.
For decades, C++ has been a cornerstone of high-performance computing, powering everything from game engines to operating systems. Today, the language continues to evolve, adapting to new challenges in security and AI-assisted development , as well as to competition from novel new languages like Rust and Carbon.
As all of this continues, C++ must adapt to the shifting tech landscape to maintain its position as one of the top programming languages.
top 10 programming languages April 2025
This article explores:
C++ 26 Preview and Major Features: What's coming in the next iteration of the language.
The Rise of AI-Assisted C++ Development: How AI is changing coding workflows.
C++ vs. Rust and Carbon: The Performance Debate in 2025: Is C++ still king?
Security and Safety: C++ in a Post-CVEs World: Best practices for secure coding.
The Future of C++ Package Management: Conan, vcpkg, and dependency trends.
C++ in Emerging Tech (Quantum, AI, Robotics): Where C++ still dominates.
C++ 26 Preview and Major Features
The C++ 26 standard, which is set to be completed in mid-2026, should be one of the most significant updates to the language in years. In this latest iteration, the focus is on safety, simplicity, and performance.Here are some key expected features.
Pattern Matching (P2392)
Pattern matching, proposed in P2392, draws inspiration from functional languages such as Rust and Haskell. This feature is anticipated to be included in C++26, offering developers a more expressive and syntactically cleaner approach to conditional logic.
The use of the proposed new pattern matching functionality in C++ 26
Figure 1. The use of the proposed new pattern matching functionality in C++ 26.
Contracts (P2900)
As part of proposal P2900, preconditions, postconditions, and assertations could finally become part of the standard, improving code reliability. P2900 is currently under consideration for possible inclusion in C++26 or a later iteration. It aims to introduce contract programming features into the language in a standardized way, and it does so by building on prior experimental work such as the withdrawn C++ 20 contracts proposal.
Example:
The use of the proposed new contracts feature in C++ 26
Figure 2. The use of the proposed new contracts feature in C++ 26.
There are a few key components of Contracts:
Preconditions:
These are checks that must be true before a function is called.
For example, a function that takes a pointer might require ptr != nullptr.
It helps catch caller-side errors early.
Postconditions:
These are checks that must be true after a function is executed.
For example, a sorting function might guarantee that the output array is in ascending order.
This ensures that the function meets its promised behavior.
Assertations:
These are checks that must be true at a specified point in the code.
For example, the verification of an intermediate computation result.
This helps detect logical errors during development.
SIMD Parallelism (std::simd)
C++ 26 proposes using standardized Single Instruction, Multiple Data(SIMD) support for high-performance computing. SIMD is a parallel computing architecture that allows a single instruction to process multiple data points simultaneously. Traditional sequential processing only allows one operation to be performed at a time, while SIMD allows a CPU to execute the same operation on multiple data elements in parallel, which significantly improves performance for tasks involving large datasets or repetitive calculations.
SIMD in action
Figure 3. SIMD in action.
Reflection and Metaprogramming (P2996)
Static reflection is a proposed C++ feature currently under discussion in proposal P2996. It would enable compile-time introspection of program structures, allowing code to inspect types, functions, variables, and other entities without runtime overhead (additional computational resources consumed by a system during program execution).
Some key benefits of static reflection and metaprogramming include:
Boilerplate reduction
Elimination of manual code generation for tasks like:
Serialization
Object-relational mapping (ORM)
Logging and debugging formatters
Compile time safety
Errors are caught during compilation and not during runtime.
Optimization opportunities
Offers smarter metaprogramming by generating optimized code paths based on type.
The use of reflection and metaprogramming
Figure 4. The use of reflection and metaprogramming.
The overall impact on developers may include a reduction in undefined behavior, improved maintainability of code, and keeping C++ at a competitive level with languages like Rust and Carbon.
The Rise of AI-Assisted C++ Development
AI-powered tools can enhance C++ coding by understanding complex templates, offering smart completions, and simplifying debugging.
AI-Powered Code Completion
Modern development tools, such as intelligent IDEs (integrated development environments) and AI-powered coding assistants, have advanced significantly in their ability to parse and interpret sophisticated C++ template metaprogramming. Unlike earlier tools that battled with template-heavy code (due to its compile-time nature and abstract syntax), contemporary systems leverage deep semantic analysis, code evaluation, and machine learning to accurately resolve template instantiations, offer context-aware suggestions, and enhance debugging and error messages.
How AI performs code completion
Figure 5. How AI performs code completion.
Automated Refactoring
Modern AI-powered coding assistants, like GitHub's Copilot , can analyze C++ code to identify risky or outdated patterns and automatically propose safer alternatives. For example:
Raw Pointers -> Smart Pointers: AI detects manual new/delete usage and suggests std::unique_ptr or std::shared_ptr to prevent memory leaks.
Uninitialized Variables: Flags uninitialized variables and recommends fixes.
const Correctness: Identifies missing const qualifiers and enforces immutability where possible.
Deprecated Functions: Gives warnings when outdated or unsafe functions are detected, such as strcpy versus strncpy, and helps modernize code.
Debugging and Optimization Hints
AI models trained on large C++ codebases can predict performance bottlenecks and other issues that can be improved and suggest optimizations. The challenges this poses, however, are the increased prevalence of false positives in complex metaprogramming and a tendency to over-rely on AI, leading to just a basic understanding of the language.
C++ vs. Rust and Carbon: The Performance Debate in 2025
Rust is known for its enforcement of memory safety at compile time, but C++ still dominates in legacy systems and with low-latency applications. Carbon, on the other hand, aims for seamless C++ interoperability, but its adoption remains limited.
performance-benchmarks.png
A coexistence strategy for these languages may include using Rust for new and safety-critical components such as cryptography and sticking to C++ for performance-critical legacy systems such as game engines.
Security and Safety: C++ in a Post-CVEs World
There are modern best practices that should be followed when programming in C++, including:
The use of std::span instead of raw pointers.
Adopting std::format over printf to avoid format-string vulnerabilities.
Enabling -Werror and static analyzers like Clang-Tidy and SonarQube.
The C++ Core Guidelines
The Microsoft Guidelines Support Library (GSL) helps ensure safety. It is a small, header-only library developed by Microsoft to support the C++ core guidelines, a set of best practices for writing safer and more maintainable C++ code. GSL provides utilities that help eliminate common sources of bugs, such as bounds violations, null pointer dereferences, and incorrect lifetime management.
Key Features of GSL for Safety Enforcement
There are a few key features of GSL for safety enforcement:
Bounds Checking with gsl::span
gsl::span replaces raw pointers and arrays with a bounds-checked view over contiguous sequences. This helps prevent overflow attacks and underflows.
Bounds checking with gsl::span
Figure 6. Bounds checking with gsl::span.
Pointer Ownership with gsl::owner
Pointer ownership with gsl::owner marks pointers that own memory much in the same way as std::unique_ptr, but for raw pointers. It helps clarify ownership semantics and avoid leaks.
Pointer ownership with gsl::owner
Figure 7. Pointer ownership with gsl::owner.
Additionally, you can implement the use of:
gsl::not_null: To ensure pointers and smart pointers are never null.
Contract Checks (Expects and Ensures): Documents and enforces preconditions and postconditions.
Lifetime Safety Utilities: gsl::final action (like std::scope_exit) for RAII-style cleanup, gsl::narrow_cast and gsl::narrow for safe numeric conversions.
Intel CET (Control-Flow Enforcement): To assist with the mitigation of ROP attacks.
Getting Started with GSL
Use #include <gsl/gsl> to include directly or link via vcpkg. GSL is particularly useful in large-scale projects where safety and clarity are critical. While some features are now part of the standard C++ library, the GSL remains a lightweight way to adopt the C++ core guidelines incrementally.
The Future of C++ Package Management
Conan versus vcpkg in 2025:
Conan vs. vcpkg
Using C++ modules reduces dependency hell. Starting with C++ 23 , you can replace traditional #include directives like #include <iostream> with import std to import the entire C++ standard library as a module. Doing this significantly improves compilation speed and reduces dependency headaches.
C++ in Emerging Tech: Quantum Computing, AI, Robotics
With AI and high-performance computing (HPC), TensorFlow and PyTorch back ends still rely on C++ for speed. With robotics and embedded systems, Robot Operating System 3 (ROS 3 - 2025) continues using C++ for real-time control. With quantum computing , Qiskit and the Intel Quantum Software Development Kit (SDK) use C++ for low-level optimizations.
Final Thoughts and Takeaways
C++ continues to dominate performance-critical applications, but its long-term relevance hinges on key factors, such as embracing modern safety features, leveraging AI-assisted tooling, and maintaining interoperability with emerging languages like Rust and Carbon.
For developers in 2025, this means combining C++'s raw performance with contemporary best practices to sustain its competitive edge.
Additional Resources and Links
About the Author
Technology Analyst
Grant Knoetze is a cybersecurity analyst with a special interest in DFIR, programming languages, incident response, red-teaming, and malware analysis. His full-time job includes teaching and instructing in various topics from basic Linux all the way through to malware incident response, and other advanced topics. He is also a speaker at various conferences worldwide.
https://github.com/Grant-Knoetze
https://www.linkedin.com/in/grant-knoetze-563b0b1b6/
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