Cross-Ecosystem Packages As Multilingual: Prevalence, Architecture, and Health
- URL: http://arxiv.org/abs/2609.14983v1
- Date: Mon, 14 Sep 2026 03:39:31 GMT
- Title: Cross-Ecosystem Packages As Multilingual: Prevalence, Architecture, and Health
- Abstract summary: Some software packages are published to multiple package ecosystems such as NPM for JavaScript and PyPI for Python.<n>Little is known about cross-ecosystem packages, especially regarding how they are structured.<n>We conduct a large-scale empirical study of over six million packages across six major ecosystems.
- Score: 1.8341543001575067
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Modern software development increasingly relies on using multiple programming languages. Some software packages are published to multiple package ecosystems such as NPM for JavaScript and PyPI for Python. Little is known about cross-ecosystem packages, especially regarding how they are structured. In this paper, we conduct a large-scale empirical study of over six million packages across six major ecosystems to understand 1) how prevalent cross-ecosystem packages are among all packages, 2) whether there are distinct source code architectural patterns that cross-ecosystem packages use, and 3) whether there are correlations between architectural patterns and project health metrics from GitHub. Results indicate that cross-ecosystem packages constitute a small but important, growing fraction of packages. We identify five distinct architectural patterns. For example, packages that implement code generation from a shared source file or use language bindings are associated with significantly higher community visibility and development activity. Based on our findings, we provide implications for package adopters, maintainers, and researchers. We envision our taxonomy being used for future investigations into several aspects of software development, such as the trade-offs between focusing on one language and translating to other languages using bindings, templating, and wrappers, versus using native code and native functions to support additional languages.
Related papers
- SoK: Towards Reproducibility for Software Packages in Scripting Language Ecosystems [0.0]
This SoK provides an overview of existing research, aiming to highlight future directions.<n>We work out key aspects in current research, systematize identified challenges for software, and map them between the ecosystems.<n>We find that the literature is sparse, focusing on few individual problems and ecosystems.
arXiv Detail & Related papers (2025-03-27T17:10:38Z) - Biomedical Open Source Software: Crucial Packages and Hidden Heroes [2.1847932422956666]
Despite the importance of scientific software for research, it is often not formally recognized and rewarded.<n>This is especially true for foundational libraries, which are hidden below packages visible to the users.<n>We propose centrality metrics for the network of software dependencies, analyze three ecosystems, and determine the packages with the highest centrality.
arXiv Detail & Related papers (2024-04-10T01:22:02Z) - Analyzing the Evolution of Inter-package Dependencies in Operating
Systems: A Case Study of Ubuntu [7.76541950830141]
An Operating System (OS) combines multiple interdependent software packages, which usually have their own independently developed architectures.
For an evolutionary effort, designers/developers of OS can greatly benefit from fully understanding the system-wide dependency focused on individual files.
We propose a framework, DepEx, aimed at discovering the detailed package relations at the level of individual binary files.
arXiv Detail & Related papers (2023-07-10T10:12:21Z) - Promises and Perils of Mining Software Package Ecosystem Data [10.787686237395816]
Third-party packages have led to the emergence of large software package ecosystems with a maze of inter-dependencies.
Understanding the infrastructure and dynamics of package ecosystems has given rise to approaches for better code reuse, automated updates, and the avoidance of vulnerabilities.
In this chapter, we review promises and perils of mining the rich data related to software package ecosystems available to software engineering researchers.
arXiv Detail & Related papers (2023-05-29T03:09:48Z) - Ecosystem Graphs: The Social Footprint of Foundation Models [64.02855828418608]
We propose Ecosystem Graphs as a documentation framework to transparently centralize knowledge of this ecosystem.
Ecosystem Graphs is composed of assets (datasets, models, applications) linked together by dependencies that indicate technical (e.g. how Bing relies on GPT-4) and social (e.g. how Microsoft relies on OpenAI) relationships.
arXiv Detail & Related papers (2023-03-28T07:18:29Z) - A New Generation of Perspective API: Efficient Multilingual
Character-level Transformers [66.9176610388952]
We present the fundamentals behind the next version of the Perspective API from Google Jigsaw.
At the heart of the approach is a single multilingual token-free Charformer model.
We demonstrate that by forgoing static vocabularies, we gain flexibility across a variety of settings.
arXiv Detail & Related papers (2022-02-22T20:55:31Z) - pymdp: A Python library for active inference in discrete state spaces [52.85819390191516]
pymdp is an open-source package for simulating active inference in Python.
We provide the first open-source package for simulating active inference with POMDPs.
arXiv Detail & Related papers (2022-01-11T12:18:44Z) - Scikit-dimension: a Python package for intrinsic dimension estimation [58.8599521537]
This technical note introduces textttscikit-dimension, an open-source Python package for intrinsic dimension estimation.
textttscikit-dimension package provides a uniform implementation of most of the known ID estimators based on scikit-learn application programming interface.
We briefly describe the package and demonstrate its use in a large-scale (more than 500 datasets) benchmarking of methods for ID estimation in real-life and synthetic data.
arXiv Detail & Related papers (2021-09-06T16:46:38Z) - An Empirical Analysis of the R Package Ecosystem [0.0]
We analyze more than 25,000 packages, 150,000 releases, and 15 million files across two decades.
We find that the historical growth of the ecosystem has been robust under all measures.
arXiv Detail & Related papers (2021-02-19T12:55:18Z) - PyHealth: A Python Library for Health Predictive Models [53.848478115284195]
PyHealth is an open-source Python toolbox for developing various predictive models on healthcare data.
The data preprocessing module enables the transformation of complex healthcare datasets into machine learning friendly formats.
The predictive modeling module provides more than 30 machine learning models, including established ensemble trees and deep neural network-based approaches.
arXiv Detail & Related papers (2021-01-11T22:02:08Z) - Biomedical and Clinical English Model Packages in the Stanza Python NLP
Library [47.47381610312517]
We introduce biomedical and clinical English model packages for the Stanza Python NLP library.
These packages offer accurate syntactic analysis and named entity recognition capabilities for biomedical and clinical text.
We show via extensive experiments that our packages achieve syntactic analysis and named entity recognition performance that is on par with or surpasses state-of-the-art results.
arXiv Detail & Related papers (2020-07-29T07:27:41Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.