💡Can We Predict the Future of Code? A Review of "TRIZ-evolution of Programming Systems"
Is the evolution of programming languages random, or does it follow a distinct, calculable law?
As developers, we often feel like we are riding a chaotic wave of new frameworks, languages, and paradigms. One day it's Object-Oriented Programming (OOP), the next it's Functional, and suddenly we are wrestling with Reactive streams. But what if I told you that this chaos isn't random?
I recently came across a fascinating paper titled "TRIZ-evolution of Programming Systems" by Victor Berdonosov, A. Zhivotova, and T. Sycheva. It attempts to do something audacious: apply the engineering laws of TRIZ (Theory of Inventive Problem Solving) to the history and future of software development.
If you are a fan of "big picture" computer science or just want to know what you might be coding in ten years, this paper is a hidden gem. Here is my review and why you should add it to your reading list.
What is TRIZ?
First, a quick primer. TRIZ (a Russian acronym for Teoriya Resheniya Izobretatelskikh Zadach) was developed by Genrich Altshuller in the 1940s. He analyzed thousands of patents and discovered that technical systems evolve not randomly, but by overcoming specific contradictions.
For example, in a car engine, you want more power (good) but that usually adds weight (bad). Innovation happens when you solve this contradiction without a compromise. The authors of this paper argue that programming systems are also artificial systems and therefore follow these same immutable laws of evolution.
The Core Insight: Code Evolves by Conflict
The paper posits that every major shift in programming—from machine code to Assembly, to C, to Java, and beyond—was triggered by a specific systemic contradiction.
The authors map out a "Tree of Evolution" for programming paradigms. Instead of just listing history, they identify the "driving force" behind each jump. For instance, the transition to Object-Oriented Programming wasn't just a stylistic choice; it was a necessary resolution to the contradiction between the growing complexity of software systems and the human limit of manageability.
Why You Should Read It
Here is why this academic paper deserves a spot on a technical blogger's radar:
It turns "Hype" into "Science": We often chase trends because they are popular. This paper provides a framework to evaluate why a technology is winning. Is it solving a fundamental contradiction (e.g., Speed vs. Memory), or is it just noise?
The "Evolutionary Map": The paper presents an evolutionary map of programming languages. It essentially treats languages like biological species that adapt to survive. Seeing C++ or Python on this map changes how you view your daily tools.
Forecasting the Future: The most exciting part of the TRIZ methodology is that it is predictive. By identifying which contradictions in current languages are still unresolved, the authors (and you, the reader) can hypothesize what the next generation of languages must look like.
Key Takeaway
The authors suggest that we are not at the end of the road. Current paradigms still have "forgotten" contradictions that are waiting to be solved. The system that solves them will be the next big thing.
If you want to stop reacting to the future and start understanding it, give this paper a read. It’s a dense but rewarding look at the DNA of the code we write every day.
Read the abstract and paper here:
