arXiv subjects

Javier Luis Cánovas Izquierdo

Publications and source records attributed to Javier Luis Cánovas Izquierdo.

12 recordsLinked to original sources

arXiv2025

Towards Automated Governance: A DSL for Human-Agent Collaboration in Software Projects

The stakeholders involved in software development are becoming increasingly diverse, with both human contributors from varied backgrounds and AI-powered agents collaborating together in the process. This situation presents unique governance challenges, particularly in Open-Source Software (OSS) projects, where explicit policies are often lacking or unclear. This paper presents the vision and foundational concepts for a novel Domain-Specific Language (DSL) designed to define and enforce rich governance policies in systems involving diverse stakeholders, including agents. This DSL offers a pathway towards more robust, adaptable, and ultimately automated governance, paving the way for more effective collaboration in software projects, especially OSS ones.

cs.SE↗

arXiv2025

Ethical Classification of Non-Coding Contributions in Open-Source Projects via Large Language Models

The development of Open-Source Software (OSS) is not only a technical challenge, but also a social one due to the diverse mixture of contributors. To this aim, social-coding platforms, such as GitHub, provide the infrastructure needed to host and develop the code, but also the support for enabling the community's collaboration, which is driven by non-coding contributions, such as issues (i.e., change proposals or bug reports) or comments to existing contributions. As with any other social endeavor, this development process faces ethical challenges, which may put at risk the project's sustainability. To foster a productive and positive environment, OSS projects are increasingly deploying codes of conduct, which define rules to ensure a respectful and inclusive participatory environment, with the Contributor Covenant being the main model to follow. However, monitoring and enforcing these codes of conduct is a challenging task, due to the limitations of current approaches. In this paper, we propose an approach to classify the ethical quality of non-coding contributions in OSS projects by relying on Large Language Models (LLM), a promising technology for text classification tasks. We defined a set of ethical metrics based on the Contributor Covenant and developed a classification approach to assess ethical behavior in OSS non-coding contributions, using prompt engineering to guide the model's output.

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arXiv2025

A Metascience Study of the Low-Code Scientific Field

In the last years, model-related publications have been exploring the application of modeling techniques across various domains. Initially focused on UML and the Model-Driven Architecture approach, the literature has been evolving towards the usage of more general concepts such as Model-Driven Development or Model-Driven Engineering. More recently, however, the term "low-code" has taken the modeling field by storm, largely due to its association with several highly popular development platforms. The research community is still discussing the differences and commonalities between this emerging term and previous modeling-related concepts, as well as the broader implications of low-code on the modeling field. In this paper, we present a metascience study of Low-Code. Our study follows a two-fold approach: (1) to analyze the composition and growth (e.g., size, diversity, venues, and topics) of the emerging Low-Code community; and (2) to explore how these aspects differ from those of the "classical" model-driven community. Ultimately, we hope to trigger a discussion on the current state and potential future trajectory of the low-code community, as well as the opportunities for collaboration and synergies between the low-code and modeling communities.

cs.SE↗

arXiv2025

Towards Modeling Human-Agentic Collaborative Workflows: A BPMN Extension

Large Language Models (LLMs) have facilitated the definition of autonomous intelligent agents. Such agents have already demonstrated their potential in solving complex tasks in different domains. And they can further increase their performance when collaborating with other agents in a multi-agent system. However, the orchestration and coordination of these agents is still challenging, especially when they need to interact with humans as part of human-agentic collaborative workflows. These kinds of workflows need to be precisely specified so that it is clear whose responsible for each task, what strategies agents can follow to complete individual tasks or how decisions will be taken when different alternatives are proposed, among others. Current business process modeling languages fall short when it comes to specifying these new mixed collaborative scenarios. In this exploratory paper, we extend a well-known process modeling language (i.e., BPMN) to enable the definition of this new type of workflow. Our extension covers both the formalization of the new metamodeling concepts required and the proposal of a BPMN-like graphical notation to facilitate the definition of these workflows. Our extension has been implemented and is available as an open-source human-agentic workflow modeling editor on GitHub.

cs.SE↗

arXiv2025

A Bot-based Approach to Manage Codes of Conduct in Open-Source Projects

The development of Open-Source Software (OSS) projects relies on the collaborative work of contributors, generally scattered around the world. To enable this collaboration, OSS projects are hosted on social-coding platforms like GitHub, which provide the infrastructure to host the code as well as the support for enabling the participation of the community. The potentially rich and diverse mixture of contributors in OSS projects makes their management not only a technical challenge, where automation tools and bots are usually deployed, but also a social one. To this aim, OSS projects have been increasingly deploying a declaration of their code of conduct, which defines rules to ensure a respectful and inclusive participatory environment in the community, being the Contributor Covenant the main model to follow. However, the broad adoption and enforcement of codes of conduct in OSS projects is still limited. In particular, the definition, deployment, and enforcement of codes of conduct is a very challenging task. In this paper, we propose an approach to effectively manage codes of conduct in OSS projects based on the Contributor Covenant proposal. Our solution has been implemented as a bot-based solution where bots help in the definition of codes of conduct, the monitoring of OSS projects, and the enforcement of ethical rules.

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arXiv2024

On the Creation of Representative Samples of Software Repositories

Software repositories is one of the sources of data in Empirical Software Engineering, primarily in the Mining Software Repositories field, aimed at extracting knowledge from the dynamics and practice of software projects. With the emergence of social coding platforms such as GitHub, researchers have now access to millions of software repositories to use as source data for their studies. With this massive amount of data, sampling techniques are needed to create more manageable datasets. The creation of these datasets is a crucial step, and researchers have to carefully select the repositories to create representative samples according to a set of variables of interest. However, current sampling methods are often based on random selection or rely on variables which may not be related to the research study (e.g., popularity or activity). In this paper, we present a methodology for creating representative samples of software repositories, where such representativeness is properly aligned with both the characteristics of the population of repositories and the requirements of the empirical study. We illustrate our approach with use cases based on Hugging Face repositories.

cs.SE↗

arXiv2024

Dynamic Provisioning of REST APIs for Model Management

Model-Driven Engineering (MDE) is a software engineering methodology focusing on models as primary artifacts. In the last years, the emergence of Web technologies has led to the development of Web-based modeling tools and model-based approaches for the Web that offer a web-based environment to create and edit models or model-based low-code solutions. A common requirement when developing Web-based modeling tools is to provide a fast and efficient way for model management, and this is particularly a hot topic in model-based system engineering. However, the number of approaches offering RESTful services for model management is still limited. Among the alternatives for developing distributed services, there is a growing interest in the use of RESTful services. In this paper, we present an approach to provide RESTful services for model management that can be used to interact with any kind of model and can be used to build a modeling platform providing modeling-as-a-service. The approach follows the REST principles to provide a stateless and scalable service.

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arXiv2023

On the Suitability of Hugging Face Hub for Empirical Studies

Background. The development of empirical studies in software engineering mainly relies on the data available on code hosting platforms, being GitHub the most representative. Nevertheless, in the last years, the emergence of Machine Learning (ML) has led to the development of platforms specifically designed for developing ML-based projects, being Hugging Face Hub (HFH) the most popular one. With over 250k repositories, and growing fast, HFH is becoming a promising ecosystem of ML artifacts and therefore a potential source of data for empirical studies. However, so far there have been no studies evaluating the potential of HFH for such studies. Objective. In this proposal for a registered report, we aim at performing an exploratory study of the current state of HFH in order to investigate its suitability to be used as a source platform for empirical studies. Method. We conduct a qualitative and quantitative analysis of HFH for empirical studies. The former will be performed by comparing the features of HFH with those of other code hosting platforms, such as GitHub and GitLab. The latter will be performed by analyzing the data available in HFH.

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arXiv2020

A Model-based Chatbot Generation Approach to Converse with Open Data Sources

The Open Data movement promotes the free distribution of data. More and more companies and governmental organizations are making their data available online following the Open Data philosophy, resulting in a growing market of technologies and services to help publish and consume data. One of the emergent ways to publish such data is via Web APIs, which offer a powerful means to reuse this data and integrate it with other services. Socrata, CKAN or OData are examples of popular specifications for publishing data via Web APIs. Nevertheless, querying and integrating these Web APIs is time-consuming and requires technical skills that limit the benefits of Open Data movement for the regular citizen. In other contexts, chatbot applications are being increasingly adopted as a direct communication channel between companies and end-users. We believe the same could be true for Open Data as a way to bridge the gap between citizens and Open Data sources. This paper describes an approach to automatically derive full-fledged chatbots from API-based Open Data sources. Our process relies on a model-based intermediate representation (via UML class diagrams and profiles) to facilitate the customization of the chatbot to be generated.

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arXiv2020

A Survey of Software Foundations in Open Source

A number of software foundations have been created as legal instruments to better articulate the structure, collaboration and financial model of Open Source Software (OSS) projects. Some examples are the Apache, Linux, or Mozilla foundations. However, the mission and support provided by these foundations largely differ among them. In this paper we perform a study on the role of foundations in OSS development. We analyze the nature, activities, role and governance of 101 software foundations and then go deeper on the 27 having as concrete goal the development and evolution of specific open source projects (and not just generic actions to promote the free software movement or similar). Our results reveal the existence of a significant number of foundations with the sole purpose of promoting the free software movement and/or that limit themselves to core legal aspects but do not play any role in the day-to-day operations of the project (e.g., umbrella organizations for a large variety of projects). Therefore, while useful, foundations do not remove the need for specific projects to develop their own specific governance, contribution and development policies. A website to help projects to choose the foundation that best fits their needs is also available.

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arXiv2019

Online division of labour: emergent structures in Open Source Software

The development Open Source Software fundamentally depends on the participation and commitment of volunteer developers to progress. Several works have presented strategies to increase the on-boarding and engagement of new contributors, but little is known on how these diverse groups of developers self-organise to work together. To understand this, one must consider that, on one hand, platforms like GitHub provide a virtually unlimited development framework: any number of actors can potentially join to contribute in a decentralised, distributed, remote, and asynchronous manner. On the other, however, it seems reasonable that some sort of hierarchy and division of labour must be in place to meet human biological and cognitive limits, and also to achieve some level of efficiency. These latter features (hierarchy and division of labour) should translate into recognisable structural arrangements when projects are represented as developer-file bipartite networks. In this paper we analyse a set of popular open source projects from GitHub, placing the accent on three key properties: nestedness, modularity and in-block nestedness -which typify the emergence of heterogeneities among contributors, the emergence of subgroups of developers working on specific subgroups of files, and a mixture of the two previous, respectively. These analyses show that indeed projects evolve into internally organised blocks. Furthermore, the distribution of sizes of such blocks is bounded, connecting our results to the celebrated Dunbar number both in off- and on-line environments. Our analyses create a link between bio-cognitive constraints, group formation and online working environments, opening up a rich scenario for future research on (online) work team assembly.

physics.soc-ph↗

arXiv2015

EMF-REST: Generation of RESTful APIs from Models

In the last years, RESTful Web services have become more and more popular as a lightweight solution to connect remote systems in distributed and Cloud-based architectures. However, being an architectural style rather than a specification or standard, the proper design of RESTful Web services is not trivial since developers have to deal with a plethora of recommendations and best practices. Model-Driven Engineering (MDE) emphasizes the use of models and model transformations to raise the level of abstraction and semi-automate the development of software. In this paper we present an approach that leverages on MDE techniques to generate RESTful services. The approach, called EMF-REST, takes EMF data models as input and generates Web APIs following the REST principles and relying on well-known libraries and standards, thus facilitating its comprehension and maintainability. Additionally, EMF-REST integrates model and Web-specific features to provide model validation and security capabilities, respectively, to the generated API. For Web developers, our approach brings more agility to the Web development process by providing ready-to-run-and-test Web APIs out of data models. Also, our approach provides MDE practitioners the basis to develop Cloud-based modeling solutions as well as enhanced collaborative support.

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