Software Ecosystem Research Articles

Parallel multi-objective evolutionary optimization based dynamic community detection in software ecosystem

Building a dynamic network in a software ecosystem and detecting its communities can not only observe the structure of the dynamic network, but also reveal the evolution of these communities. However, previous methods cannot timely and accurately detect its communities. In view of this, we propose a method of dynamic community detection based on parallel multi-objective evolutionary optimization in this paper. In the proposed method, a dynamic network in a software ecosystem is first built based on the relationship between entities. The relationship is often time-dependent. Then, changed/unchanged connected components of the current network and time-dependent/independent sub-networks are obtained by recognizing the change of this network. Further, previous communities of each unchanged connected component remain unchanged, whereas ones of each time-dependent sub-network are detected based on parallel multi-objective evolutionary optimization. In this way, communities of each changed connected component are obtained based on ones of the time-dependent sub-network and previous ones of the time-independent sub-network, and ones of the current network after the change are formed. Five dynamic networks in a software ecosystem are built using data crawled in GitHub. Based on them, a series of experimental results demonstrate that the proposed method is advantageous.

Turnover of Companies in OpenStack: Prevalence and Rationale

To achieve commercial goals, companies have made substantial contributions to large open-source software (OSS) ecosystems such as OpenStack and have become the main contributors. However, they often withdraw their employees for a variety of reasons, which may affect the sustainability of OSS projects. While the turnover of individual contributors has been extensively investigated, there is a lack of knowledge about the nature of companies’ withdrawal. To this end, we conduct a mixed-methods empirical study on OpenStack to reveal how common company withdrawals were, to what degree withdrawn companies made contributions, and what the rationale behind withdrawals was. By analyzing the commit data of 18 versions of OpenStack, we find that the number of companies that have left is increasing and even surpasses the number of companies that have joined in later versions. Approximately 12% of the companies in each version have exited by the next version. Compared to the sustaining companies that joined in the same version, the withdrawn companies tend to have a weaker contribution intensity but contribute to a similar scope of repositories in OpenStack. Through conducting a developer survey, we find four aspects of reasons for companies’ withdrawal from OpenStack: company, community, developer, and project. The most common reasons lie in the company aspect, i.e., the company either achieved its goals or failed to do so. By fitting the survival analysis model, we find that commercial goals are associated with the probability of the company’s withdrawal, and that a company’s contribution intensity and scale are positively correlated with its retention. Maintaining good retention is important but challenging for OSS ecosystems, and our results may shed light on potential approaches to improve company retention and reduce the negative impact of company withdrawal.

Exploring three-way group decisions with consensus evolution network for software ecosystem hierarchical criteria health rating

The appropriate rating of software ecosystem health is to the benefit of its sustainable development. The rating method based on an expert panel with specialised knowledge is reliable for rating software ecosystem health. Complexity often causes obstacles for expert panels to give appropriate ratings. Facing complexity, hierarchical criteria system provides evaluation guides with multiple levels and multiple perspectives. However, at present, effective group decision-making under hierarchical criteria system remains a challenge. Thus, this article systematically investigates consensus reaching process and rating method under hierarchical criteria system of software ecosystem health, which are two important components of group decision-making. To master the consensus situation of all criteria and consensus relationships of pair-wise experts under hierarchical criteria system, we construct hierarchical consensus evolution network. Then, we further propose a novel consensus degree measurement and design a consensus reaching process with pair-wise adjustment by utilising hierarchical characteristics. For rating software ecosystem health efficiently, there are usually three ratings including health, sub-health and ill-health. Three-way decisions exactly provide semantic interpretation for these three ratings. Meanwhile, three-way decisions can reduce the risk of incorrect ratings. Considering these advantages, we develop three-way group decisions with hierarchical consensus evolution network to comprehensively rate software ecosystem health under hierarchical criteria system. Finally, take the health rating of the software ecosystem on GitHub as an example, we develop a series of experiment analysis to verify the effectiveness of the proposed method.

Evaluating the COSMOS Software Ecosystem for Domain-Specific Construction Process Simulation

Modeling and simulation are generally performed through software systems built upon a formalism (e.g., Petri Nets, DEVS). These formalisms lend themselves well to composition and leveraging expertise across domains. In contrast, domain-specific solutions utilize the language of the domain, allowing domain-experts to apply their knowledge more effectively. However, composability and universality are lost. COSMOS is a domain-specific software ecosystem. It is designed for construction processes, allowing engineers to express solutions in the language of the domain. However, unlike most domain-specific solutions, COSMOS is built upon a standard formalism (specifically, Petri Nets), retaining the advantages of general-purpose tools. In this manuscript, we evaluate the COSMOS, comparing it to both domain-specific and general-purpose approaches. Our goal is to determine whether COSMOS satisfies the simulation requirements; i.e., expressing all the required constructs and meeting result accuracy. To answer this research question, we perform three experiments, modeling: (1) horizontal earth-boring operation, (2) concreting and waste-handling process, and (3) drainage tunnel excavation and concrete placing, on COSMOS and competing simulators. Results suggest COSMOS precisely meets the results of all other evaluated tools, suggesting that it is a viable solution for the modeling and simulation of construction processes, and offering expressive advantages for domain-experts.

TIMSCONVERT: a workflow to convert trapped ion mobility data to open data formats.

Advances in mass spectrometry have led to the development of mass spectrometers with ion mobility spectrometry capabilities and dual-source instrumentation; however, the current software ecosystem lacks interoperability with downstream data analysis using open-source software and pipelines. Here, we present TIMSCONVERT, a data conversion high-throughput workflow from timsTOF Pro/fleX mass spectrometer raw data files to mzML and imzML formats that incorporates ion mobility data while maintaining compatibility with data analysis tools. We showcase several examples using data acquired across different experiments and acquisition modalities on the timsTOF fleX MS. TIMSCONVERT and its documentation can be found at https://github.com/gtluu/timsconvert and is available as a standalone command-line interface tool for Windows and Linux, NextFlow workflow and online in the Global Natural Products Social (GNPS) platform. Supplementary data are available at Bioinformatics online.

Code comment generation based on graph neural network enhanced transformer model for code understanding in open-source software ecosystems

Code comment generation based on graph neural network enhanced transformer model for code understanding in open-source software ecosystems

Special Issue on Software Health of Software Ecosystems

Special Issue on Software Health of Software Ecosystems

Pyspeckit: A Spectroscopic Analysis and Plotting Package

pyspeckit is a toolkit and library for spectroscopic analysis in Python. We describe the pyspeckit package and highlight some of its capabilities, such as interactively fitting a model to data, akin to the historically widely-used splot function in IRAF. pyspeckit employs the Levenberg–Marquardt optimization method via the mpfit and lmfit implementations, and important assumptions regarding error estimation are described here. Wrappers to use pymc and emcee as optimizers are provided. A parallelized wrapper to fit lines in spectral cubes is included. As part of the astropy affiliated package ecosystem, pyspeckit is open source and open development, and welcomes input and collaboration from the community.

Digital Platform Ecosystem Dynamics: The Roles of Product Scope, Innovation, and Collaborative Network Centrality

This research highlights the circulative nature of digital platform ecosystem dynamics. Investigating these dynamics, we examine the mutual influence between participants’ product scope and product innovation over time and probe the moderating role of co-created collaborative networks. We distinguish between two types of product innovation: new product development and existing product updates. Our longitudinal analysis of the Hadoop software ecosystem indicates that participants covering a broader scope of the platform’s technological layers are less likely to develop new products but more likely to update existing products. In turn, participants with more frequent new product development are more likely to expand their product scope, whereas those with more frequent existing product updates are less likely to pursue scope expansion. Participants’ centrality in the ecosystem’s collaborative network amplifies the bidirectional link between product scope and existing product updates but weakens the link between product scope and new product development. Our findings offer a theoretical and practical understanding of temporal dynamics between participants’ product scope choices and different forms of product innovations in the co-created collaborative network environment.

The DIARieS ecosystem – A software ecosystem to simplify discovery, implementation, analysis, reproducibility, and sharing of scientific results and environments in Heliophysics

The infrastructure of the Heliophysics discipline has promising components but with several missing gaps, drastically reducing research and development efficiency. Developing an online discovery and analysis software ecosystem will close several of these gaps. The five main focuses on this ecosystem should be Discovery, Implementation, Analysis, Reproducibility, and Sharing of results (DIARieS). In this paper, we give a detailed description of how the proposed software ecosystem should operate, and point out the large range of possible applications to benefit many disparate groups, such as researchers, operational staff, decision-makers, and educators. The infrastructure components and technological capabilities necessary for its completion are either currently available or in development, making such an ecosystem possible for the first time. One main focus of current infrastructure investments must be to adapt and connect these pieces together into a cohesive whole to increase our research and development efficiency.

Collaboration in software ecosystems: A study of work groups in open environment

As a particular type of software ecosystem, an open source software ecosystem (OSSECO) is a collection of interdependent open source software (OSS) projects which are developed and evolve together. Events happening within an OSSECO inherently involve the collaboration of participants from multiple OSS projects, forming a temporary work group. However, it is still unclear how different members of a work group collaborate to fix cross-project bugs, a typical event in the maintenance of OSSECOs. This study aims to investigate the characteristics of collaboration within a work group when fixing cross-project bugs in an OSSECO. It involves the participants from the upstream (which caused the bugs) and the downstream (which were affected by the bugs) OSS projects. We conducted our study on 236 cross-project bugs from the scientific Python ecosystem, involving 571 participants and 91 OSS projects, to understand open collaboration within a work group. We established a quantitative analysis to investigate the members of a work group, along with a qualitative analysis to understand the roles of the members from different OSS communities. The results show that: (1) A typical work group is constituted of four to eight members from the core development teams of the two OSS communities. More members concern with the upstream OSS projects and few can make active contributions to both sides; (2) Distinct responsibilities are taken by the two OSS communities, with the downstream members as the problem-finders and the upstream members as the decision-makers or gatekeepers. Our findings reveal the collaborative mechanism and the responsibility allocation between the upstream and downstream OSS communities in the ecosystems. • A study on 236 cross-project bug fixing activities to understand open collaboration in open source software ecosystems. • Six findings that reveal the members of a cross-project bug fixing work group. • Five findings that summarize the roles of cross-project bug fixing group members. • Recommendations to the researchers, developers, and practitioners.

Exploring causal relationships in proteomic profiles in Cytoscape using the CausalPath App

Introduction: CausalPath compares experimentally measured changes in molecular profiles against curated biological pathways and infers causality between changes in measured features from profiling experiments (e.g., RNA-seq or proteomics from total or phospho-protein levels). Methods: We developed the CausalPath Cytoscape App, an app (i.e., plugin) for visualizing results from the CausalPath method within the Cytoscape Java-based desktop network analysis and visualization platform. Use Cases: Users are given instruction that represents use cases in multiple cancer research areas through the visualization of CausalPath analysis results generated from data by the Clinical Proteomic Tumor Analysis Consortium. Discussion: The CausalPath Cytoscape App visualizes the set of known interactions that are supported by molecular profiling data via the CausalPath method. This integration of CausalPath and Cytoscape benefits users interested in performing secondary analyses (e.g., module detection) on the sub-networks that result from CausalPath analysis by utilizing the many analytical features available in the Cytoscape software ecosystem.

Towards unified retrieval system for GLAM institutions in India: Designing a prototype for biblio-cultural information space

Generally, the galleries, libraries, archives, and museums (GLAM) of developing countries use two different information representation and retrieval systems to manage bibliographic datasets and cultural-heritage objects. These software-centric systems create different retrieval silos, and end users need to hop from one retrieval interface to another with diverse search techniques for an all-encompassing search. A centrally indexed biblio-cultural information system in place of multiple retrieval silos, as a single-window search mechanism for bibliographic and cultural resources, may help users of GLAM find the required information at ease. This study is an attempt to design a technical framework towards this goal of a unified system of retrieval by applying different domain-specific open-source applications related to a library software ecosystem, and open standards. The methodology, based on open-source software and open standards, may well be adopted by libraries with complex information management needs.

Integration process simulator: A tool for performance evaluation of task scheduling of integration processes

ABSTRACT Due to large volumes of data from Cloud Computing and from the Internet of Things, the companies’ software ecosystem requires an efficient integration of applications and services. Performance improvement from integration platforms’ runtime systems is directly related to task scheduling strategies from integration processes. It is still a challenge to find the proper heuristic for a given integration process subject to high inbound data rates. This article proposes a simulation tool for the field of Enterprise Application Integration, which implements different scheduling heuristics and allows the extraction of performance metrics. Three task scheduling heuristics were simulated during the integration process, and the results were evaluated through statistical tests.

Demonstrating and negotiating the adoption of web design technologies: Cascading Style Sheets and the CSS Zen Garden

Cascading Style Sheets (CSS) express the visual design of a website through code and remain an understudied area of web history. Although CSS was proposed as a method of adding a design layer to HTML documents early on in the development of the web, they only crossed from a marginal position to mainstream usage after a long period of proselytising by web designers working towards “web standards”. The CSS Zen Garden grassroots initiative aimed at negotiating, mainstreaming and archiving possible methods of CSS web design, while dealing with varying levels of browser support for the technology. Using the source code of the CSS Zen Garden and the accompanying book, this paper demonstrates that while the visual designs were complex and sophisticated, the CSS lived within an ecosystem of related platforms, i.e., web browsers, screen sizes and design software, which constrained its use and required enormous sensitivity to the possibilities browser ecosystems could reliably provide. As the CSS Zen Garden was maintained for over ten years, it also acts as a unique site to trace the continuing development of web design, and the imaginaries expressed in the Zen Garden can also be related to ethical dimensions that influence the process of web design. Compared to Flash-based web design, work implemented using CSS required a greater willingness to negotiate source code configurations between browser platforms. Following the history of the individuals responsible for creating and contributing to the CSS Zen Garden shows the continuing influence of layer-based metaphors of design separated from content within web source code.

An interoperable software ecosystem to store, visualize, and publish water resources systems modelling data

Water systems modelers have developed multiple, independent, model- and study-area specific tools to store, query, visualize, and share their data. This fragmentation makes difficult comparisons, and synthesis within or across study areas. This paper identifies the common components of four existing tools for data storage, web visualization, and repository, and relates them correctly in syntax and semantics. Connecting the tools in a state-of-the-art, open-source software ecosystem allowed comparing the effects of population growth and water conservation in simulation and optimization models for the Bear River Watershed, U.S. and Monterrey, Mexico that have different spatial coverage and urban and agricultural representations. The software ecosystem also publishes the models and their data for discovery. The software ecosystem can help modelers tap the best features of individual software tools to answer a next generation of water management questions that seek to discover, use, reproduce, extend, compare, or synthesize within or across study areas.

Toward Remaking Software Development to Secure It

Modern software development depends on tools and techniques to represent implied information processing logic to the human engineer, relying chiefly on effortful human reasoning to best determine critical properties of the software system. Current conceptualization, visualization and contextualization of software in development amounts to a significant under-utilization of already limited development resources directed to optimization, prevention, and addressing fundamental security properties of the software system. As a step toward increasing such utilization as a basis for a global ecosystem of secure software, this work explores and evaluates an alternative representation of software source code for the sake of secure development, manifesting universal, critical properties of the system to enhance control of security factors while the bulk of the properties of the system are being determined and the costly skills of the developer are directed to the many aspects of the task.

Problematic Technology Use: The impact of personality and continued use

Modern software development depends on tools and techniques to represent implied information processing logic to the human engineer, relying chiefly on effortful human reasoning to best determine critical properties of the software system. Current conceptualization, visualization and contextualization of software in development amounts to a significant under-utilization of already limited development resources directed to optimization, prevention, and addressing fundamental security properties of the software system. As a step toward increasing such utilization as a basis for a global ecosystem of secure software, this work explores and evaluates an alternative representation of software source code for the sake of secure development, manifesting universal, critical properties of the system to enhance control of security factors while the bulk of the properties of the system are being determined and the costly skills of the developer are directed to the many aspects of the task.

Reuse and maintenance practices among divergent forks in three software ecosystems

With the rise of social coding platforms that rely on distributed version control systems, software reuse is also on the rise. Many software developers leverage this reuse by creating variants through forking, to account for different customer needs, markets, or environments. Forked variants then form a so-called software family; they share a common code base and are maintained in parallel by same or different developers. As such, software families can easily arise within software ecosystems, which are large collections of interdependent software components maintained by communities of collaborating contributors. However, little is known about the existence and characteristics of such families within ecosystems, especially about their maintenance practices. Improving our empirical understanding of such families will help build better tools for maintaining and evolving such families. We empirically explore maintenance practices in such fork-based software families within ecosystems of open-source software. Our focus is on three of the largest software ecosystems existence today: Android, .NET, and JavaScript. We identify and analyze software families that are maintained together and that exist both on the official distribution platform (Google play, nuget, and npm) as well as on GitHub , allowing us to analyze reuse practices in depth. We mine and identify 38 software families, 526 software families, and 8,837 software families from the ecosystems of Android, .NET, and JavaScript, to study their characteristics and code-propagation practices. We provide scripts for analyzing code integration within our families. Interestingly, our results show that there is little code integration across the studied software families from the three ecosystems. Our studied families also show that techniques of direct integration using git outside of GitHub is more commonly used than GitHub pull requests. Overall, we hope to raise awareness about the existence of software families within larger ecosystems of software, calling for further research and better tools support to effectively maintain and evolve them.

CSDMS: a community platform for numerical modeling of Earth surface processes

Abstract. Computational modeling occupies a unique niche in Earth and environmental sciences. Models serve not just as scientific technology and infrastructure but also as digital containers of the scientific community's understanding of the natural world. As this understanding improves, so too must the associated software. This dual nature – models as both infrastructure and hypotheses – means that modeling software must be designed to evolve continually as geoscientific knowledge itself evolves. Here we describe design principles, protocols, and tools developed by the Community Surface Dynamics Modeling System (CSDMS) to promote a flexible, interoperable, and ever-improving research software ecosystem. These include a community repository for model sharing and metadata, interface and ontology standards for model interoperability, language-bridging tools, a modular programming library for model construction, modular software components for data access, and a Python-based execution and model-coupling framework. Methods of community support and engagement that help create a community-centered software ecosystem are also discussed.