Software metrics are used to measure code quality, code debugging, and performance optimization in computer programming are examples. There are several tools and methods to check source code aspects such as density, complexity, reliability, and other code properties. Halstead and McCabe’s Cyclomatic complexity are the most popular metrics for measuring the density and complexity of the code. Worth mentioning the work’s Maclennan, which tackles transformational metrics to measure the complexity of the relationship between the syntax and semantics of a language.  The idea is to select two or more metrics to verify code in C++ and Rust languages written by humans and ChatGPT. First, to write code for implementing data structures, such as arrays, lists, and binary three. Next, verify these codes, according to the metrics selected.

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