SIMULSCRIPT
Simulscript

Introducing SimulScript – a powerful and efficient code comparison tool designed to streamline your workflow. Utilizing advanced cosine similarity analysis, SimulScript enables you to effortlessly compare and identify similarities between code snippets.

How does it work?

Hold on to your glasses, because we're about to dive into the magic behind SimulScript

Tokenization
SimulScript breaks down the code snippets into smaller parts such as keywords, variables, and symbols. This process is known as tokenization, which is the first step in converting the text-based code into a numerical format.
Vectorization
In this stage, each token from the tokenization process is assigned a numerical value. These values are then used to create a vector representation of the code snippet in a high-dimensional space. This allows the algorithm to compare and analyze the code snippets more effectively.
Cosine Similarity Calculation:
The dot product of the vectors is determined, and this value represents the cosine of the angle between the vectors. This value is then normalized by the magnitude of each vector, resulting in a cosine similarity score between -1 and 1. This score indicates the level of similarity between the code snippets, with a higher score indicating a greater degree of similarity.

If ou still do not totally understand how it works , You could take a look at the code , or learn more from this wikipedia page ↗ Here, I only found this out when i was trying to get into machine learning as well

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