Data Validation in C++: Libraries and Examples

Data Validation in C++: Overview of Libraries and Practical Examples

In modern C++ development, data validation is one of the key stages in processing user input, network requests, or configuration files. Without reliable checking, an application becomes vulnerable to incorrect data, which can lead to crashes, memory leaks, or logical errors. In this article, we will look at the main approaches and popular libraries for data validation in C++.

Why is Validation Needed?

Validation solves three main tasks:

Security — preventing the input of malicious data (SQL injections, buffer overflow).
Correctness — ensuring that data matches the expected format (email, phone number, age).
Stability — eliminating failures during type conversion (e.g., string to number).

Libraries for Validation in C++

Let's look at several popular solutions that can be used in C++ projects.

1. Boost.LexicalCast — Simple Number Checking

The Boost.LexicalCast library allows you to safely convert strings to numbers and vice versa. On error, it throws a boost::bad_lexical_cast exception.

#include <boost/lexical_cast.hpp>#include <iostream>#include <string>

bool isValidNumber(const std::string& input) {    try {        int value = boost::lexical_cast<int>(input);        return (value >= 0 && value <= 100);    } catch (const boost::bad_lexical_cast&) {        return false;    }}

int main() {    std::cout << isValidNumber("50") << std::endl;   // 1    std::cout << isValidNumber("abc") << std::endl; // 0    return 0;}

2. PicoJSON — Validating JSON Structures

For checking JSON data, the lightweight PicoJSON library is often used. It allows you to parse JSON and check for the presence of required fields.

#include "picojson.h"#include <iostream>#include <string>

bool validateUserJSON(const std::string& jsonStr) {    picojson::value val;    std::string err = picojson::parse(val, jsonStr);    if (!err.empty()) return false;

    picojson::object& obj = val.get<picojson::object>();    // Check for the presence of the "name" field of type string    if (obj.count("name") == 0 || !obj["name"].is<std::string>()) return false;    // Check the "age" field — must be a number and > 0    if (obj.count("age") == 0 || !obj["age"].is<double>()) return false;    double age = obj["age"].get<double>();    if (age <= 0 || age > 150) return false;    return true;}

int main() {    std::string valid = R"({"name":"Alice","age":30})";    std::string invalid = R"({"name":"Bob","age":-5})";    std::cout << validateUserJSON(valid) << std::endl;   // 1    std::cout << validateUserJSON(invalid) << std::endl; // 0    return 0;}

3. Validator Pattern (Custom Implementation)

If you need a flexible validation rule, you can implement your own validator class. Example for checking an email address:

#include <regex>#include <string>#include <iostream>

class EmailValidator {public:    bool validate(const std::string& email) const {        // Simplest regular expression for email        static const std::regex pattern(R"([a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\\.[a-zA-Z]{2,})");        return std::regex_match(email, pattern);    }};

int main() {    EmailValidator ev;    std::cout << ev.validate("user@example.com") << std::endl; // 1    std::cout << ev.validate("invalid-email") << std::endl;     // 0    return 0;}