Treffer: The innovation dynamics of programming technologies.

Title:
The innovation dynamics of programming technologies.
Authors:
Borchers C; School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA., Braesemann F; Oxford Internet Institute, University of Oxford, Oxford, UK.; Einstein Center Digital Future (ECDF) , Berlin, Germany.; Complexity Science Hub , Vienna, Austria.; DWG Data Science Company , Berlin, Germany.
Source:
Journal of the Royal Society, Interface [J R Soc Interface] 2025 Dec 01; Vol. 22 (233).
Publication Type:
Journal Article
Language:
English
Journal Info:
Publisher: Royal Society Country of Publication: England NLM ID: 101217269 Publication Model: Print Cited Medium: Internet ISSN: 1742-5662 (Electronic) Linking ISSN: 17425662 NLM ISO Abbreviation: J R Soc Interface Subsets: MEDLINE
Imprint Name(s):
Original Publication: London : Royal Society, [2004]-
Contributed Indexing:
Keywords: complexity science; innovation; networks; software; success prediction; technology
Entry Date(s):
Date Created: 20260115 Date Completed: 20260115 Latest Revision: 20260115
Update Code:
20260117
DOI:
10.1098/rsif.2025.0166
PMID:
41537863
Database:
MEDLINE

Weitere Informationen

Programming technologies evolve rapidly. Yet, the factors related to the rise and fall of programming technologies have not yet been revealed. To close this gap, we study innovation in programming by analysing data from the online coding platform Stack Overflow. Our aim is to understand how competition affects the growth trajectories of technology tags over time. Using correlation networks that encode dynamic tag usage patterns, we identify two robust technology clusters. They represent (i) core computing facilities covering operating systems, databases and servers, and (ii) application development technologies, containing frameworks for web development and machine learning. We find that declining old technologies are primarily associated with the core computing facilities cluster, while rising new technologies are mainly associated with the cluster of application development technologies. We derive common factors associated with the rise and fall of technology tags on the platform: technologies that link positively to other new technologies and negatively to any frequently used, old technology have higher chances of gaining traction and becoming successful. We conclude that popular, rising technologies tend to supplement rather than complement existing technologies. The empirical findings point towards creative destruction as a mechanism that shapes the innovation dynamics of programming technologies.
(© 2025 The Authors.)