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A Cultural Diffusion Model for the Rise and Fall of Programming Languages
Sergi Valverde1, Ricard V Solé1
11 ICREA-Complex Systems Lab, Universitat Pompeu Fabra, Barcelona, Spain.
Human Biology
|March 3, 2016
Summary
Programming languages (PLs) drive technology evolution. A new model explains PL adoption, rise, and fall based on programmer choices and community influence, highlighting innovation diffusion.
Area of Science:
- Computer Science
- Information Technology
- Computational Linguistics
Background:
- Programming languages (PLs) are crucial for human-computer interaction and have shaped IT history since the 1950s.
- Like natural languages, PLs evolve, with new ones emerging and old ones becoming extinct.
- A diversity of PLs has always coexisted, each occupying specific niches and competing for users.
Purpose of the Study:
- To model the statistical patterns of programming language adoption, rise, and fall.
- To understand the factors influencing the diffusion of programming language innovations.
Main Methods:
- Developed a simple model simulating programmer behavior regarding PL adoption.
- The model considers programmers choosing to use existing PLs or not.
- Analyzed statistical patterns of language emergence, growth, and decline.
Main Results:
- The model successfully accounts for the observed statistical patterns of PL adoption and evolution.
- Programmer decisions to adopt existing PLs used by others significantly impact diffusion.
- Strong communities of practice play a key role in the spread of PL innovations.
Conclusions:
- Programmer community dynamics are a primary driver in the success and failure of programming languages.
- The study provides insights into the evolutionary dynamics of technological innovations, using PLs as a case study.
- Understanding these patterns can inform the development and adoption strategies for future programming languages.
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