C++20 introduced several game-changing improvements to the language and its Standard Template Library (STL). One particularly useful addition was the introduction of the std::erase_if function, which simplifies common patterns involving filtering elements from containers. However, using erase_if with mutable predicates can lead to unexpected and inconsistent behavior across compiler versions and different implementations of the standard library.

In this detailed guide, we’ll explore why std::erase_if behaves unusually when paired with mutable predicate lambdas, why the behavior can vary across older versus newer compilers, and best practices you should follow to avoid issues. Whether you’re a seasoned veteran in C++ or someone new aiming to understand subtle language nuances, this guide is designed to help you write predictable, reliable code regardless of your compiler version.

Understanding std::erase_if and the Use of Predicates

What Exactly is std::erase_if?

Introduced in C++20, std::erase_if simplifies removing elements from standard containers such as std::vector, std::map, and std::list. It eliminates common boilerplate code typically associated with implementing the “erase-remove” idiom.

Here’s a basic example demonstrating typical use:

#include <vector>
#include <iostream>
#include <algorithm>

int main() {
    std::vector<int> vec{1, 2, 3, 4, 5, 6};
    std::erase_if(vec, [](int val) {
        return val % 2 == 0; // Erase even numbers
    });

    for (int i : vec)
        std::cout << i << ' '; // Output: 1 3 5
}

Understanding Predicate Functions and Mutable Lambdas

A predicate function evaluates a condition and returns a boolean value. Standard library algorithms, like erase_if, use predicates to decide whether to keep or discard elements.

Lambdas are often popular predicate choices, especially due to their conciseness. A lambda marked as mutable can change the state of its captures. Consider this mutable lambda:

int counter = 0;
auto mutable_lambda = [counter]() mutable {
    ++counter; 
    return (counter % 2 == 0);
};

Here the mutable lambda maintains internal state and modifies it each time it’s called. It’s allowed to modify its internal data because it’s explicitly declared mutable.

How std::erase_if is Typically Implemented: The Erase-Remove Idiom

Under the hood, almost all standard library vendors implement erase_if using the erase-remove idiom:

1. Call std::remove_if to relocate elements to erase, typically at the container’s end.
2. Erase these undesirable elements all at once via container.erase.

The typical pseudo-implementation looks something like:

template <class Container, class Predicate>
auto erase_if(Container& container, Predicate pred) {
    auto it = std::remove_if(container.begin(), container.end(), pred);
    return container.erase(it, container.end());
}

But as we’ll see next, subtle nuances arise when mutable lambdas are used with such algorithms.

Deep Dive: Compiler and Standard Library Implementation Differences (Older vs Newer)

Why Are Mutable Predicate Lambdas Problematic?

A key issue is that the C++ Standard does not guarantee how many times or in what specific order the predicate can be called by the algorithm—in essence, the predicate may be called multiple times for evaluation or in a non-linear fashion. If you use mutable lambdas that depend on internal state, you could experience unpredictable results.

Compiler and Standard Library Version Differences

Different standard library implementations like the GNU libstdc++, LLVM libc++, and the Microsoft MSVC STL may vary in how exactly they invoke predicates and handle internal iterators. Older compiler/libstdc++ environments often differ substantially compared to newer versions.

Practical Observations from Stack Overflow Discussions & Real-Life Examples

Users on Stack Overflow reported this exact confusing scenario:

• Using mutable lambdas with std::erase_if caused distinctly different behaviors in older versions of GCC (e.g., GCC 9, GCC 10) compared with newer versions (GCC 12, GCC 13).
• While using Clang with libc++ delivered completely different behaviors as compared to GCC’s libstdc++ implementation.

Here’s a simplified example to illustrate the scenario encountered:

std::vector<int> vec{1,2,3,4,5};
int count = 0;
std::erase_if(vec,[count](int x) mutable{
    return (++count > 2);
});

• Older compiler behavior: erratic, unpredictable results.
• Newer compiler behavior: more predictable, yet still not universally consistent across implementations.

Understanding the C++ Standard and Its Requirements

The C++ Standard documentation explicitly mentions that the algorithm predicates must not depend on the number of times they’re called or on their relative order. Thus, relying on mutable state in predicate lambdas triggers unspecified behavior—not undefined behavior outright, but nevertheless implementation-specific and unpredictable behavior.

Simply put, while your code may compile and run, the outcome can vary significantly depending on your compiler or STL vendor library.

Best Practices When Using Mutable Predicates with STL Algorithms

To ensure your code remains robust and highly portable, follow these best practices:

1. Avoid Stateful Mutable Lambdas With Algorithms

Prefer stateless lambdas or pure functions as predicates when applying standard algorithms, including erase_if.

2. If You Need Mutable State, Manage It Explicitly Yourself

Rather than relying on mutable lambdas, explicitly control state changes in a predictable manner outside predicate functions.

3. Always Consult Your Compiler and Library Documentation

Different compilers/STL implementations may clearly document such cases. Knowing standard documentation helps avoid pitfalls.

Recommended Code Example Illustrating Robust Approach

Consider explicitly handling state externally to your predicate function. Here’s a robust and portable version of our previous example:

#include <vector>
#include <iostream>
#include <algorithm>

int main() {
    std::vector<int> vec{1,2,3,4,5};
    int count = 0;

    auto threshold_reached = [&count]() {
        return (++count > 2);
    };

    std::erase_if(vec, [&threshold_reached](int) {
        return threshold_reached();
    });

    for(auto &item : vec) { // Predictable output: always removes after the second element.
        std::cout << item << ' ';
    }
}

FAQs About Mutable Predicates and Compiler Behaviors

Q1: What exactly does mutable mean in a lambda predicate?

A mutable lambda allows internal state modification of captured variables even though captured by value.

Q2: Why is my code behaving differently across compilers when I use mutable lambdas with standard algorithms?

Because the standard doesn’t specify the exact number or ordering of predicate invocations, STL implementations can differ.

Q3: Is this considered a compiler bug?

No, this is not a bug but an implementation-specific, standard-compliant behavior. The standard explicitly leaves this scenario unspecified.

Q4: Should mutable lambdas as algorithm predicates always be avoided?

In general, yes—prefer stateless predicates. Stateful lambdas create scenarios that are inherently unpredictable across STL implementations.

Q5: How many times can STL algorithms call predicates?

Algorithms may call predicates multiple times for each element, without guaranteed ordering.

Q6: How can I ensure consistent behavior?

Always use pure functions or stateless lambdas, handle mutable states explicitly, and verify your compiler documentation.

Conclusion: Key Takeaways for Reliable STL Predicate Usage

In summary, using mutable lambdas with C++20’s std::erase_if can create unpredictable behavior across compilers due to unspecified standards-compliant differences in library implementation. This nuanced issue highlights the importance of understanding standard specifications and adhering to clear coding guidelines.

Recommended Best Practices:

• Limit lambdas predicates to stateless use-cases.
• Explicitly handle mutable state outside the predicate context.
• Review both your compiler’s and the standard’s documentation.

C++ provides power and flexibility, but understanding subtle nuances like these ensures that code remains reliable across environments.

References and Additional Resources

• Official C++ standard documentation
• Original Stack Overflow discussion
• libstdc++ Documentation
• LLVM libc++ documentation
• MSVC STL Documentation

By following these insights, you’ll achieve stable results, higher portability, and increased robustness in your modern C++ applications.