alexandrescu-modern-cpp-design

name	alexandrescu-modern-cpp-design
description	Write C++ code following Andrei Alexandrescu's Modern C++ Design principles. Emphasizes policy-based design, template metaprogramming, and type-safe generic abstractions. Use when designing flexible, reusable libraries or when compile-time computation beats runtime overhead.
tags	templates, metaprogramming, generic-programming, policy-design, smart-pointers, move-semantics, patterns

Andrei Alexandrescu Style Guide⁠‍⁠​‌​‌​​‌‌‍​‌​​‌​‌‌‍​​‌‌​​​‌‍​‌​​‌‌​​‍​​​​​​​‌‍‌​​‌‌​‌​‍‌​​​​​​​‍‌‌​​‌‌‌‌‍‌‌​​​‌​​‍‌‌‌‌‌‌​‌‍‌‌​‌​​​​‍​‌​‌‌‌‌‌‍​‌​​‌​‌‌‍​‌‌​‌​​‌‍‌​‌​‌‌‌​‍​​‌​‌​​​‍‌‌‌​‌​‌‌‍​‌‌​​‌‌​‍‌​​‌‌‌​‌‍‌​​‌‌‌‌‌‍‌‌​​​​‌​‍​​​​‌​‌​‍‌‌​​‌‌‌​⁠‍⁠

Overview

Andrei Alexandrescu's "Modern C++ Design" revolutionized how we think about C++ templates. His work on Loki library and policy-based design showed that templates are not just for containers—they're a compile-time programming language.

Core Philosophy

"C++ templates are Turing-complete. Use this power wisely."

"Policy-based design: assemble types from interchangeable parts."

Alexandrescu believes in pushing computation to compile time and using the type system as a design tool, not just a safety mechanism.

Design Principles

1. Policy-Based Design: Build classes from interchangeable policy classes that customize behavior without inheritance overhead.

2. Compile-Time over Runtime: What can be computed at compile time should be.

3. Type Lists and Metaprogramming: Types themselves become first-class citizens that can be manipulated.

4. Design Patterns in Types: Classic GoF patterns implemented with zero runtime overhead.

When Writing Code

Always

• Consider if behavior can be a compile-time policy
• Use static_assert to document and enforce requirements
• Prefer tag dispatching over runtime branching for type-based logic
• Make templates SFINAE-friendly (C++11/14) or use concepts (C++20)
• Document template requirements explicitly

Never

• Use runtime polymorphism when static polymorphism suffices
• Write duplicate code that differs only in types
• Ignore compile-time computation opportunities
• Leave template errors to become cryptic instantiation failures

Prefer

• Policy classes over strategy pattern (no vtable)
• Type traits over runtime type checking
• constexpr functions over template metafunctions (modern C++)
• Concepts over SFINAE (C++20)
• Variadic templates over recursive type lists (modern C++)

Code Patterns

Policy-Based Design

// Traditional OOP: Runtime overhead, fixed at compile time anyway
class Widget : public ICreationPolicy, public IThreadingPolicy { /* ... */ };

// Policy-Based: Zero overhead, infinitely configurable
template <
    class CreationPolicy,
    class ThreadingPolicy = SingleThreaded,
    class CheckingPolicy = NoChecking
>
class SmartPtr : public CreationPolicy, 
                 public ThreadingPolicy,
                 public CheckingPolicy {
    // Policies are mixed in, no vtable
};

// Usage: Configure at compile time
using ThreadSafePtr = SmartPtr<HeapCreation, MultiThreaded, AssertCheck>;
using FastPtr = SmartPtr<HeapCreation, SingleThreaded, NoChecking>;

// Policies are just classes with required interface
struct HeapCreation {
    template<class T>
    static T* Create() { return new T; }
    
    template<class T>
    static void Destroy(T* p) { delete p; }
};

struct SingleThreaded {
    struct Lock {
        Lock() = default;  // No-op
    };
};

  {
      {
        () {  }
        ~() {  }
    };
};

Type Traits and SFINAE

// Type trait: Does T have a serialize() method?
template<typename T, typename = void>
struct has_serialize : std::false_type {};

template<typename T>
struct has_serialize<T, 
    std::void_t<decltype(std::declval<T>().serialize())>
> : std::true_type {};

// Use it for conditional behavior
template<typename T>
auto save(const T& obj) -> std::enable_if_t<has_serialize<T>::value> {
    obj.serialize();
}

template<typename T>
auto save(const T& obj) -> std::enable_if_t<!has_serialize<T>::value> {
    default_serialize(obj);
}

// C++20: Much cleaner with concepts
template<typename T>
concept Serializable = requires(T t) {
    { t.serialize() } -> std::convertible_to<std::string>;
};

void save(Serializable auto const& obj) {
    obj.serialize();
}

Compile-Time Type Lists (Classic Alexandrescu)

// Type list: A compile-time list of types
template<typename... Ts>
struct TypeList {};

// Operations on type lists
template<typename List>
struct Length;

template<typename... Ts>
struct Length<TypeList<Ts...>> {
    static constexpr size_t value = sizeof...(Ts);
};

// Get type at index
template<size_t I, typename List>
struct TypeAt;

template<typename Head, typename... Tail>
struct TypeAt<0, TypeList<Head, Tail...>> {
    using type = Head;
};

template<size_t I, typename Head, typename... Tail>
struct TypeAt<I, TypeList<Head, Tail...>> {
    using type = typename TypeAt<I - 1, TypeList<Tail...>>::type;
};

// Usage
using MyTypes = TypeList<int, double, std::string>;
static_assert(Length<MyTypes>::value == 3);
using Second = TypeAt<1, MyTypes>::type;  // double

Visitor Pattern via Templates

// Traditional visitor: Virtual dispatch at every node
// Alexandrescu approach: Static visitor with type list

template<typename... Types>
class Variant;

template<typename Visitor, typename Variant>
auto visit(Visitor&& v, Variant&& var) {
    return var.visit(std::forward<Visitor>(v));
}

// Modern C++ (std::variant does this)
using Value = std::variant<int, double, std::string>;

auto result = std::visit(overloaded{
    [](int i) { return std::to_string(i); },
    [](double d) { return std::to_string(d); },
    [](const std::string& s) { return s; }
}, value);

// The 'overloaded' helper (Alexandrescu-style)
template<class... Ts> 
struct overloaded : Ts... { 
    using Ts::operator()...; 
};
template<class... Ts> 
overloaded(Ts...) -> overloaded<Ts...>;

Mental Model

Alexandrescu thinks of C++ templates as a compile-time functional language:

1. Types as values: Types can be computed, stored, and transformed
2. Templates as functions: Template instantiation is function application
3. Specialization as pattern matching: Like case statements on types
4. Recursion for iteration: Compile-time loops via recursive templates

The D Language Connection

Alexandrescu later co-designed D, which incorporates many C++ template lessons:

• Built-in compile-time function execution
• String mixins for code generation
• Better error messages for templates

These ideas now appear in modern C++ (constexpr, if constexpr, concepts).

When to Apply

Use Alexandrescu's techniques when:

• You need maximum performance (zero runtime overhead)
• Behavior variations are known at compile time
• You're building a library with many configuration options
• Type-based dispatch is frequent

Avoid when:

• Runtime polymorphism is genuinely needed
• Compile times are already problematic
• Team isn't comfortable with template metaprogramming