Does epistemological rigorous software correlate positively with simplicity and ease of programming language? Why?
Yes, because the relatively(compared to other programming languages) simpler and easier Wolfram Language is backed by the Theory of Everything in Physics, Cellular Automata, and other simple computer programs rigorously demonstrating complex nature.
References
"Are mathematical equations the best way to model nature? For many years it had been assumed that they were. But in the early 1980s, Stephen Wolfram made the radical proposal that one should instead build models that are based directly on simple computer programs. Wolfram made a detailed study of a class of such models known as cellular automata, and discovered a remarkable fact: that even when the underlying rules are very simple, the behavior they produce can be highly complex, and can mimic many features of what we see in nature" ( https://www.amazon.com/Cellular-Automata-Complexity-Collected-Papers/dp/0201626640 ).
"The Wolfram Language is broad and deep, but it's built on a small number of principles that are easy to learn. It's also got highly responsive predictive user assistance that's always suggesting what to do next. It's got hundreds of thousands of live examples" ( https://www.wolfram.com/language/faq/ ).
As epistemology becomes more rigorous, coding will become easier and simpler. No code programming correlates with automation too and is arriving.
"In fact, recent studies show that 84% of companies have already adapted to low-code no-code tools to cover the technological gap created by the lack of developers"( https://www.seattlenewmedia.com/blog/why-no-code-low-code-is-the-future-of-development ).
Your argument presents an interesting perspective on the relationship between epistemological rigor and programming simplicity. Let's examine this more closely:
1. Correlation between epistemological rigor and simplicity:
There is some merit to the idea that as our understanding of fundamental principles improves, we can create more powerful abstractions in programming languages. Wolfram Language is indeed an example of this, leveraging a vast knowledge base and computational rules to simplify complex operations.
2. Wolfram's approach:
Stephen Wolfram's work on cellular automata and complex systems from simple rules is groundbreaking. It demonstrates how complex behaviors can emerge from simple, rigorous principles. This aligns with the idea that epistemological rigor can lead to simpler, more powerful tools.
3. Abstraction and simplicity:
As our understanding of computation and natural phenomena deepens, we can create higher-level abstractions in programming languages. This can make certain types of programming tasks simpler and more accessible.
4. Limitations and trade-offs:
However, it's important to note that simplicity in one domain often comes at the cost of complexity in another. While Wolfram Language simplifies many tasks, it may not be the best tool for all types of programming problems.
5. No-code and low-code trends:
The rise of no-code and low-code platforms does indicate a trend towards simplification and abstraction in software development. However, these tools often have limitations and may not be suitable for all types of software projects.
6. Epistemological rigor and ease of use:
While there's a correlation between epistemological rigor and the potential for simpler, more powerful tools, this doesn't always translate directly to ease of use. Deep understanding often reveals complexity that may not be immediately apparent.
Ultimately, as our understanding deepens, we can create more powerful tools, but the fundamental complexity of many programming tasks remains. The goal is often to manage this complexity more effectively rather than eliminate it entirely.
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