Identifying Unmaintained Projects in GitHub

Background: Open source software has an increasing importance in modern software development. However, there is also a growing concern on the sustainability of such projects, which are usually managed by a small number of developers, frequently working as volunteers. Aims: In this paper, we propose an approach to identify GitHub projects that are not actively maintained. Our goal is to alert users about the risks of using these projects and possibly motivate other developers to assume the maintenance of the projects. Method: We train machine learning models to identify unmaintained or sparsely maintained projects, based on a set of features about project activity (commits, forks, issues, etc). We empirically validate the model with the best performance with the principal developers of 129 GitHub projects. Results: The proposed machine learning approach has a precision of 80%, based on the feedback of real open source developers; and a recall of 96%. We also show that our approach can be used to assess the risks of projects becoming unmaintained. Conclusions: The model proposed in this paper can be used by open source users and developers to identify GitHub projects that are not actively maintained anymore.Comment: Accepted at 12th International Symposium on Empirical Software Engineering and Measurement (ESEM), 10 pages, 201

Role of Newcomers Supportive Strategies on Socio-Technical Performance of Open Source Projects

The success of open source software (OSS) projects have been studied in previous research. This paper focused on the effect of newcomers’ supportive strategies in OSS projects on the success level of the projects. Our research analyzes the socio-technical commitment to the project as a proxy for success. Data about 453 OSS projects from GitHub.com is collected and analyzed to empirically test the research model. We have applied a clustering technique to explore the dataset attributes. Results show the importance of newcomers’ supportive strategies on the different socio-technical aspects of OSS projects’ leading to success. Also, we have tested the effect of programming language diversity and project profile health on the success of projects. The outcome of this study has both managerial and practical implications

Why We Engage in FLOSS: Answers from Core Developers

The maintenance and evolution of Free/Libre Open Source Software (FLOSS) projects demand the constant attraction of core developers. In this paper, we report the results of a survey with 52 developers, who recently became core contributors of popular GitHub projects. We reveal their motivations to assume a key role in FLOSS projects (e.g., improving the projects because they are also using it), the project characteristics that most helped in their engagement process (e.g., a friendly community), and the barriers faced by the surveyed core developers (e.g., lack of time of the project leaders). We also compare our results with related studies about others kinds of open source contributors (casual, one-time, and newcomers).Comment: Accepted at CHASE 2018: 11th International Workshop on Cooperative and Human Aspects of Software Engineering (8 pages

Supporting Comparison of Developer Profiles across Online Communities

Current software development practices leave a plethora of activities that are archived in version control systems, issue trackers, mailing lists, or Question and Answer (Q&A) forums. Software managers are increasingly using these online activities to better evaluate job candidates. We introduce our tool, Visual Resume, that displays visual overviews of developers’ contributions in code sharing sites (e.g. GitHub) and Q&A forums (e.g. Stack Overflow). The design of the tool is broadly applicable as an approach to summarize and display online contributions.KEYWORDS: software engineering, hiring decisions, online community, Computer programmer

Dificultades de los “recién llegados” a proyectos software en ejecución

No es poco frecuente que, en los proyectos software, sea necesario incorporar nuevos desarrolladores en una etapa avanzada de su ejecución. En estas circunstancias, estos “recién llegados” enfrentan varias dificultades y desafíos que les impiden comenzar rápidamente a contribuir, con sus conocimientos y experiencia previos, a la marcha del proyecto. Este artículo reporta los resultados de un estudio exploratorio-descriptivo dirigido a identificar las dificultades a las que se enfrentan los nuevos miembros del equipo de proyecto al unirse a un proyecto en ejecución, así como identificar las acciones que usualmente se adoptan para mitigar estos problemas y dificultades. El estudio revela que la escasa o nula documentación y la necesidad de conocer el producto en construcción son las principales dificultades, mientras que la asignación de un referente y la provisión de capacitación se mencionan como las principales acciones que las organizaciones suelen tomar para mitigar esos problemas.XIV Workshop de Ingeniería de Software (WIS).Red de Universidades con Carreras en Informática (RedUNCI

An Empirical Study of Bots in Software Development -- Characteristics and Challenges from a Practitioner's Perspective

Software engineering bots - automated tools that handle tedious tasks - are increasingly used by industrial and open source projects to improve developer productivity. Current research in this area is held back by a lack of consensus of what software engineering bots (DevBots) actually are, what characteristics distinguish them from other tools, and what benefits and challenges are associated with DevBot usage. In this paper we report on a mixed-method empirical study of DevBot usage in industrial practice. We report on findings from interviewing 21 and surveying a total of 111 developers. We identify three different personas among DevBot users (focusing on autonomy, chat interfaces, and "smartness"), each with different definitions of what a DevBot is, why developers use them, and what they struggle with. We conclude that future DevBot research should situate their work within our framework, to clearly identify what type of bot the work targets, and what advantages practitioners can expect. Further, we find that there currently is a lack of general purpose "smart" bots that go beyond simple automation tools or chat interfaces. This is problematic, as we have seen that such bots, if available, can have a transformative effect on the projects that use them.Comment: To be published at the ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE