Preliminary Survey on Empirical Research Practices in Requirements Engineering

Context and Motivation:\ud Based on published output in the premium RE conferences and journals, we observe a growing body of research using both quantitative and qualitative research methods to help understand which RE technique, process or tool work better in which context. Also, more and more empirical studies in RE aim at comparing and evaluating alternative techniques that are solutions to common problems. However, until now there have been few meta studies of the current state of knowledge about common practices carried out by researchers and practitioners in empirical RE. Also, surprisingly little has been published on how RE researchers perceive the usefulness of these best practices.\ud \ud Objective:\ud The goal of our study is to improve our understanding of what empirical practices are performed by researchers and practitioners in RE, for the purpose of understanding the extent to which the research methods of empirical software engineering are adopted in the RE community.\ud \ud Method:\ud We surveyed the practices that participants of the REFSQ conference have been using in their empirical research projects. The survey was part of the REFSQ 2012 Empirical Track.\ud \ud Conclusions:\ud We found that there are 15 commonly used practices out of a set of 27. The study has two implications: first it presents a list of practices that are commonly used in the RE community, and a list of practices that still remain to be practiced. Researchers may now make an informed decision on how to extend the practices they use in producing and executing their research designs, so that their designs get better. Second, we found that senior researchers and PhD students do not always converge in their perceptions about the usefulness of research practices. Whether this is all right and whether something needs to be done in the face of this finding remains an open question

Un procedimiento de medición de tamaño funcional para especificaciones de requisitos

Hoy en día el tamaño del software es utilizado en la gestión y control de producción como uno de los parámetros esenciales de los modelos de estimación que contribuyen a la calidad de los proyectos de software y productos entregables. Aunque la importancia de la medición temprana del tamaño es evidente, actualmente esta medición es solamente alcanzada en fases tardías del ciclo de vida del software (análisis, diseño e implementación). El tamaño de software puede ser cuantificado usando diferentes técnicas, como las líneas de código y los métodos de medición de tamaño funcional. Un método de medición de tamaño funcional mide el tamaño del software cuantificando los requisitos funcionales. El método Análisis de Puntos de Función (FPA) es el método mayormente utilizado. Este método fue desarrollado para medir Sistemas de Información de Gestión desarrollados con metodos tradicionales. Aunque IFPUG FPA ha ido alcanzado mayor popularidad en la industria, este método carece de aplicabilidad a todo tipo de software y a nuevos paradigmas de desarrollo. Para direccionar estas debilidades, COSMIC-FFP ha surgido como un método de segunda generación y ha sido probado como un estandar internacional (ISO/IEC 19761). Sin embargo, la generalidad de COSMIC-FFP requiere ser instanciado por medio de un procedimiento más específico y sistemático en conjunción con un método de desarrollo de software.Condori Fernández, ON. (2007). Un procedimiento de medición de tamaño funcional para especificaciones de requisitos [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/1998Palanci

Towards a FAIR Dataset for Spanish Non-Functional Requirements

Cursos e Congresos, C-155[Abstract] Supervised Machine Learning algorithms (ML) have enhanced the performance of the automatic non-functional requirements (NFR) classification in the Requirements Engineering domain. However, the lack of public datasets, dealing with imbalanced datasets and reproducibility are current concerns in ML experiments. We conducted a quasi-experiment to generate a dataset of NFR in the Spanish Language, following the FAIR Principles. We collected 109 requirements from an open access repository of the University of A Coru˜ na, and performed a labeling process based in the categories and subcategories of the ISO/IEC 25010 quality model. Using a Fleiss’ Kappa test we obtained a substantial agreement (0.78) at the category level and a moderate agreement (0.48) when the classification is per subcategory supervised Machine Learning algorithms (ML) have enhanced the performance of the automatic non-functional requirements (NFR) classification in the Requirements Engineering domain. However, the lack of public datasets, dealing with imbalanced datasets and reproducibility are current concerns in ML experiments. We conducted a quasi-experiment to generate a dataset of NFR in the Spanish Language, following the FAIR Principles. We collected 109 requirements from an open access repository of the University of A Coruña, and performed a labeling process based in the categories and subcategories of the ISO/IEC 25010 quality model. Using a Fleiss’ Kappa test we obtained a substantial agreement (0.78) at the category level and a moderate agreement (0.48) when the classification is per subcategoryCITIC is funded by the Xunta de Galicia through the collaboration agreement between the Conseller ´ıa de Cultura, Educaci´on, Formaci´on Profesional e Universidades and the Galician universities for the reinforcement of the research centres of the Galician University System (CIGUS

UN ANÁLISIS SOBRE LA ADOPCIÓN EN LA INDUSTRIA DE UN PROCEDIMIENTO DE MEDICIÓN CONFORME A LA ISO/IEC 19761

RESUMENEste artículo presenta un análisis de la probabilidad de adoptar un procedimiento de medición llamado RmFFP. Este procedimiento de medición es conforme al método estándar ISO/IEC 19761 y ha sido definido para estimar el tamaño funcional a partir de artefactos de software de alto nivel que son especificadas con OO-Method, un método de generación automática basado en la transformación de modelos. El análisis fue llevado a cabo en base a los constructores del Modelo de Adopción de Métodos, tales como la facilidad de uso percibida, utilidad percibida e intención de uso, los cuales permitieron evaluar las percepciones e intenciones de los “usuarios” que usan RmFFP. Un estudio experimental fue rigurosamente diseñado, el mismo que fue replicado con estudiantes de doctorado en ingeniería de software con la finalidad de mejorar la fiabilidad de los resultados. Para este fin, algunas modificaciones fueron llevadas a cabo exitosamente sobre el instrumento experimental (cuestionario) utilizado para la captura de las percepciones e intenciones de los usuarios. Los resultados obtenidos, tanto en el primer estudio como en su replicación, corroboraron empíricamente que RmFFPes percibido como útil y fácil de usar. Así mismo la intención a ser usado en el futuro para medir el tamaño funcional de especificaciones de requisitos fue también verificado. PALABRAS CLAVEModelo de Adopción de MétodosProcedimiento de MediciónTamaño FuncionalISO/IEC 19761 ABSTRACTThis paper presents an analysis on the likelihood of adoption of a measurement procedure called RmFFP. This measurement procedure is compliant to the standard method ISO/IEC 19761, which was defined to estimate the functional size from software artefacts specified at early stage of the OO-Method process. OO-Method is an automatic generation method based on the models transformation. The analysis was carried out in basis of the constructors of the Method Adoption Model, such as ease of use perceived, usefulness perceived, and intention to use, which allowed evaluating the perceptions and intentions of the measurers that using RmFFP. An experimental study was designed rigorously, which was also replicated with PhDstudents in software engineering with the purpose of improving the reliability of the results. For this purpose, some modifications were carried out on the experimental instrument (survey), which was used to capture the perceptions and intentions of the users. The results obtained in the first study and replication; confirm empirically that RmFFP is perceived as useful and easy of use. In addition, the intention to be used in the future for measuring the functional size of requirements specifications was also verified. KEYWORDSMethod Adoption ModelMeasurement procedureFunctional sizeISO/IEC 1976

An Action Research for Improving the Sustainability Assessment Framework Instruments

[Abstract] In the last years, software engineering researchers have defined sustainability as a quality requirement of software, but not enough effort has been devoted to develop new methods/techniques to support the analysis and assessment of software sustainability. In this study, we present the Sustainability Assessment Framework (SAF) that consists of two instruments: the software sustainability–quality model, and the architectural decision map. Then, we use participatory and technical action research in close collaboration with the software industry to validate the SAF regarding its applicability in specific cases. The unit of analysis of our study is a family of software products (Geographic Information System- and Mobile-based Workforce Management Systems) that aim to address sustainability goals (e.g., efficient collection of dead animals to mitigate social and environmental sustainability risks). The results show that the sustainability–quality model integrated with the architectural decision maps can be used to identify sustainability–quality requirements as design concerns because most of its quality attributes (QAs) have been either addressed in the software project or acknowledged as relevant (i.e., creating awareness on the relevance of the multidimensional sustainability nature of certain QAs). Moreover, the action–research method has been helpful to enrich the sustainability–quality model, by identifying missing QAs (e.g., regulation compliance, data privacy). Finally, the architectural decision maps have been found as useful to guide software architects/designers in their decision-making process.This work has received partial support by Xunta de Galicia/FEDER-UE CSI (ED431G/01, ED431C 2017/58); Xunta de Galicia/FEDER-UE, ConectaPeme, GEMA (IN852A 2018/14); MINECO-AEI/FEDER-UE with the projects: Datos 4.0 (TIN2016-78011-C4-1-R), BIZDEVOPS (RTI2018-098309-B-C32), FLATCITY (TIN2016-77158-C4-3-R.); and FONDECYT with the Kusisqa project (014-2019-FONDECYTBM-INC.INV)Xunta de Galicia; ED431G/01Xunta de Galicia; ED431C 2017/58Xunta de Galicia; IN852A 2018/14Gobierno de Chile; 014-2019-FONDECYTBM-INC.IN

Towards an Experimental Framework for Measuring Usability of Model-Driven Tools 1

Abstract. According to the Model-Driven Development (MDD) paradigm, analysts can substantially improve the software development process concentrating their efforts on a conceptual model, which can be transformed into code by means of transformation rules applied by a model compiler. However, MDD tools are not widely used in industry. One of the reasons for this poor adoption is the lack of usability of MDD tools. This paper presents a framework to evaluate the usability of such tools. The framework will be used as a basis for a family of experiments to get clear insights into the barriers to usability that prevent MDD tools from being widely adopted in industry

Replication Data Management,needs and solutions: an initial evaluation of conceptual approaches for integrating heterogeneous replication study data

Replication Data Management (RDM) aims at enabling the use of data collections from several iterations of an experiment. However, there are several major challenges to RDM from integrating data models and data from empirical study infrastructures that were not designed to cooperate, e.g., data model variation of local data sources. [Objective] In this paper we analyze RDM needs and evaluate conceptual RDM approaches to support replication researchers. [Method] We adapted the ATAM evaluation process to (a) analyze RDM use cases and needs of empirical replication study research groups and (b) compare three conceptual approaches to address these RDM needs: central data repositories with a fixed data model, heterogeneous local repositories, and an empirical ecosystem. [Results] While the central and local approaches have major issues that are hard to resolve in practice, the empirical ecosystem allows bridging current gaps in RDM from heterogeneous data sources. [Conclusions] The empirical ecosystem approach should be explored in diverse empirical environments