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Abstract The software engineering community aims to achieve and maintain high‐efficient software engineering practical activities. One of the techniques used for this purpose is Test‐Driven Development (TDD), which is a cyclic and test‐centered development method positively related to maintainability, which may vary depending on the context and application. Previous research has indicated that TDD's benefits on maintainability may be due to the improved focus on coding and testing activities. However, limited research has investigated the role of engagement in software quality. Therefore, this study investigates the relationship between TDD methods, engagement level in development activities, and maintainability. The primary research questions addressed in this study are does following TDD methods improve the engagement level in development activities? And does a higher engagement level leads to better maintainability? The study employs a statistical analysis technique, regression analysis to explore the research questions. The results show that TDD behaviours improve the engagement level, and engaging in development activities has a significant positive impact on maintainability. Additionally, the study finds that the positive impact of focussing on testing, such as writing more test cases, is more pronounced compared to coding activities. Our study adds to current software engineering literature that not only personal expertise but the engagement level in the development process are associated with software quality and calls for the emphasis on developer's engagement.

Abstract As more and more software teams use online issue tracking systems to collaborate on software projects, the accurate assignment of new issues to the most suitable contributors may have significant impact on the success of the project. As a result, several research efforts have been directed towards automating this process to save considerable time and effort. However, most approaches focus mainly on software bugs and employ models that do not sufficiently take into account the semantics and the non‐textual metadata of issues and/or produce models that may require manual tuning. A methodology that extracts both textual and non‐textual features from different types of issues is designed, providing a Jira dataset that involves not only bugs but also new features, issues related to documentation, patches, etc. Moreover, the semantics of issue text are effectively captured by employing a topic modelling technique that is optimised using the assignment result. Finally, this methodology aggregates probabilities from a set of individual models to provide the final assignment. Upon evaluating this approach in an automated issue assignment setting using a dataset of Jira issues, the authors conclude that it can be effective for automated issue assignment.

Great strides have been made to encourage researchers to archive data created by research and provide the necessary systems to support their storage. Additionally it is recognised that data are meaningless unless their provenance is preserved, through appropriate meta-data. Alongside this is a pressing need to ensure the quality and archiving of the software that generates data, through simulation, control of experiment or data-collection and that which analyses, modifies and draws value from raw data. In order to meet the aims of reproducibility we argue that data management alone is insufficient: it must be accompanied by good software practices, the training to facilitate it and the support of stakeholders, including appropriate recognition for software as a research output.

Feedback from software users, such as bug reports, is vital in the management of software projects. In GitHub, the feedback is typically expressed as new issues. Through filing issue reports, users may help identify and fix bugs, document software code, and enhance software quality via feature requests. In this paper, we aim at investigating some characteristics of issues to facilitate issue management and software management. We investigate the important degrees of behaviors that are related to issues in popular projects to assess the importance of issues in GitHub and analyze the effectiveness of issue labeling for issue handling. Then, we explore the patterns of issue commits over time in popular projects based on visual analysis and obtain the following results: we find that the behaviors that are related to issues play important roles in the GitHub. We also find that the time distribution of issue commits follows a three-period development model, which approximately corresponds to the project life cycle. These results may provide a new knowledge about issues that can help managers manage and allocate project resources more effectively and even reduce software failures.

The processes involved in requirements engineering are some of the most, if not the most, important steps in systems development. The need for well-defined requirements remains a critical issue for the development of any system. Describing the structure and behavior of a system could be proven vague, leading to uncertainties, restrictions, or improper functioning of the system that would be hard to fix later. In this context, this article proposes SENSE, a framework based on standardized expressions of natural language with well-defined semantics, called boilerplates, that support a flow-down procedure for requirement management. This framework integrates sets of boilerplates and proposes the most appropriate of them, depending, among other considerations, on the type of requirement and the developing system, while providing validity and completeness verification checks using the minimum consistent set of formalities and languages. SENSE is a consistent and easily understood framework that allows engineers to use formal languages and semantics rather than the traditional natural languages and machine learning techniques, optimizing the requirement development. The main aim of SENSE is to provide a complete process of the production and standardization of the requirements by using semantics, ontologies, and appropriate NLP techniques. Furthermore, SENSE performs the necessary verifications by using SPARQL (SPIN) queries to support requirement management.

Transcriptomic reconstructions without reference (i.e., de novo) are common for data samples derived from non-model biological systems. These assemblies involve massive parallel short read sequence reconstructions from experiments, but they usually employ ad-hoc bioinformatic workflows that exhibit limited standardization and customization. The increasing number of transcriptome assembly software continues to provide little room for standardization which is exacerbated by the lack of studies on modularity that compare the effects of assembler synergy. We developed a customizable management workflow for de novo transcriptomics that includes modular units for short read cleaning, assembly, validation, annotation, and expression analysis by connecting twenty-five individual bioinformatic tools. With our software tool, we were able to compare the assessment scores based on 129 distinct single-, bi- and tri-assembler combinations with diverse k-mer size selections. Our results demonstrate a drastic increase in the quality of transcriptome assemblies with bi- and tri- assembler combinations. We aim for our software to improve de novo transcriptome reconstructions for the ever-growing landscape of RNA-seq data derived from non-model systems. We offer guidance to ensure the most complete transcriptomic reconstructions via the inclusion of modular multi-assembly software controlled from a single master console.

Este texto aporta una reflexión teórica, fundada en una investigación y discusión de la literatura internacional, sobre el porvenir y la evolución del trabajo y sus transformaciones. Con él se aporta una fundamentación concreta y empírica a los recurrentes debates sobre la llamada 'sociedad de la información', tomando como base el trabajador colectivo de la producción de software. Trabajador que se utiliza reiteradamente como muestra de un porvenir dorado de las sociedades centrales que se extenderá, por la deslocalización, a las sociedades 'emergentes' o en desarrollo. Donde el trabajo inmaterial deparará un futuro lleno de esperanzas. En contraposición con esa visión idealizada, y siguiendo una línea de trabajo ya mostrada en anteriores estudios, las tendencias puestas en evidencia, en el despliegue de las fábricas de software en España, son muy semejantes a las que se detectan en la realidad internacional. Una de las preocupaciones fundamentales de la investigación ha sido el acercarse a lo que realmente sucede. A cómo se desarrollan las nuevas organizaciones productivas en la fabricación de software, para así poder identificar las grandes líneas de tendencia, el destino, del presente y del futuroque espera a los trabajadores del sector del software. Unos trabajadores y trabajadoras que resultan ser emblemática representación de cuanto se discute actualmente sobre el porvenir del trabajo en la sociedad de la información. Lo ponemos en evidencia es que la tendencia a separar concepción de ejecución, con una reiteración renovada de la división del trabajo entre empresas, o entre centros de trabajo de la misma empresa, es una marca fuerte de los desarrollos en curso. La parte más 'noble', la toma de requisitos, el análisis, el contacto directo con el cliente final queda en un lado. En el otro, en las factorías, tendencialmente, acaba llevándose a cabo el "desarrollo puro y duro". El núcleo fundamental de nuestro argumento está vinculado a la exploración de los tipos de trabajo trasladados, de las posibilidades para los lugares donde se desplazan o crean estas nuevas factorías, del papel que pueden jugar en el fomento o la creación misma de círculos virtuosos de creación de riqueza y de trabajo decente y cualificado. De posibilidades para los territorios sociales en los que se implantan. Tratamos de abrir reflexiones y problemáticas de fondo de la sociología del trabajo. Porque los trabajos desplazados, cualificados sí, pero pagados con salarios mucho más bajos, y que necesitan altas dosis de saber, conocimiento, técnica y experiencia, están acabando en los polos lejanos de la 'nueva' división internacional del trabajo.