Computational theories should be made with natural language instead of meaningless code

Area of Science:

• Computer Science
• Philosophy of Language

Background:

• The target article proposes using code to resolve ambiguities in natural language for understanding property.
• This contrasts with established practices in computer programming that emphasize natural language for code readability.

Purpose of the Study:

• To critique the claim that code enhances property understanding by resolving natural language ambiguity.
• To analyze the implications of meaningless code on the discussability of Boyer's theory.

Main Methods:

• Comparative analysis of natural language ambiguity vs. code ambiguity.
• Examination of programming best practices regarding variable and function naming.
• Logical critique of the target article's central argument.

Main Results:

• Natural language, when used for variables and functions, enhances code clarity and reduces ambiguity.
• Arbitrary code, conversely, introduces significant ambiguity, hindering comprehension.
• The abstract nature of the target article's theory, due to its reliance on 'meaningless code,' obstructs rigorous debate.

Conclusions:

• The assertion that code clarifies property understanding is challenged by programming principles favoring natural language.
• Meaningless code renders theoretical arguments obscure and difficult to evaluate.
• Effective communication in both programming and theoretical discourse benefits from clear, descriptive language.