Biblioteca Digital de Sistedes
Bienvenidos a la Biblioteca Digital de Sistedes, donde ponemos a disposición de nuestros socios y del público en general los fondos documentales asociados a las actividades de nuestra sociedad. Además, como principal valor, esta biblioteca contiene el archivo de actas de las Jornadas Sistedes celebradas desde 2015. Las actas de las jornadas precedentes, que se remontan al año 1996, se irán incluyendo en la medida de lo posible.
La biblioteca también incluye otros documentos de producción propia, como los boletines de noticias que publicamos desde febrero de 2018, o los vídeos de nuestros seminarios, donde presentamos charlas de interés para la comunidad científica. Puedes encontrar todos estos documentos y vídeos en nuestro Archivo documental.
Nuestros archivos
Seleccione una comunidad o categoría para explorar sus archivos.
- Sistedes pone a disposición de sus miembros y simpatizantes su archivo documental, en el que se incluyen todo tipo de publicaciones (boletines de prensa, seminarios, documentos, informes, etc.) que puedan ser de interés para las comunidades de Ingeniería del Software, Bases de Datos y Tecnologías de Desarrollo de Software.
- Los servicios software se están convirtiendo en un factor clave en el crecimiento de cualquier economía. Este hecho ha motivado en los últimos tiempos el interés de los distintos actores económicos por desarrollar lo que se ha denominado la «Ciencia de los Servicios», también conocida desde una perspectiva más amplia como «Ciencia, Gestión e Ingeniería de los Servicios» (SSME). Se trata de una llamada a la acción dirigida principalmente a la Universidad, la Industria informática y la Administración pública, con el propósito final de crear principios, conocimiento, métodos y técnicas para articular sus respectivas responsabilidades y actividades en torno al concepto de servicio.
- Las Jornadas de Ingeniería del Software y Bases de Datos (JISBD) constituyen un foro de encuentro de referencia donde investigadores y profesionales de España, Portugal e Iberoamérica en los campos de la Ingeniería del Software y de las Bases de Datos pueden debatir e intercambiar ideas, crear sinergias y, sobre todo, conocer la investigación que se está llevando a cabo en nuestra comunidad.
- Las Jornadas de PROgramación y LEnguajes (PROLE) constituyen un marco propicio de reunión, debate y divulgación para los grupos españoles que investigan en temas relacionados con la programación y los lenguajes de programación. Con la organización de este evento nacido en 2001, de carácter anual, se pretende fomentar el intercambio de experiencias y resultados, así como la comunicación y cooperación entre dichos grupos.
Jornadas destacadas
Las XIX Jornadas de Ciencia e Ingeniería de Servicios (JCIS 2024) se han celebrado en A Coruña del 17 al 19 de junio de 2024, como parte de las Jornadas Sistedes.
El programa de JCIS 2024 se ha organizado en torno a sesiones temáticas o tracks.
Las XXVIII Jornadas de Ingeniería del Software y Bases de Datos (JISBD 2024) se han celebrado en A Coruña del 17 al 19 de junio de 2024, como parte de las Jornadas Sistedes.
El programa de JISBD 2024 se ha organizado en torno a sesiones temáticas o tracks.
Las XXIII Jornadas de Programación y Lenguajes (PROLE 2024) se han celebrado en A Coruña del 17 al 19 de junio de 2024, como parte de las Jornadas Sistedes.
El programa de PROLE 2024 se ha organizado en torno a sesiones temáticas o tracks.
Las Jornadas de la Sociedad de Ingeniería de Software y Tecnologías de Desarrollo de Software (Sistedes) se han celebrado en A Coruña del 17 al 19 de junio de 2024, como parte del VII Congreso Español de Informática (CEDI 2024).
Últimas publicaciones
A Deep Learning Model for Natural Language Querying in Cyber-Physical Systems
Llopis, Juan Alberto; Fernández-García, Antonio Jesús; Criado, Javier; Iribarne, Luis; Ayala, Rosa; Z. Wang, James. Actas de las XXVIII Jornadas de Ingeniería del Software y Bases de Datos (JISBD 2024), 2024-06-17.
As a result of technological advancements, the number of IoT devices and services is rapidly increasing. Due to the increasing complexity of IoT devices and the various ways they can operate and communicate, finding a specific device can be challenging because of the complex tasks they can perform. To help find devices in a timely and efficient manner, in environments where the user may not know what devices are available or how to access them, we propose a recommender system using deep learning for matching user queries in the form of a natural language sentence with Web of Things (WoT) devices or services. The Transformer, a recent attention-based algorithm that gets superior results for natural language problems, is used for the deep learning model. Our study shows that the Transformer can be a recommendation tool for finding relevant WoT devices in Cyber-Physical Systems (CPSs). With hashing as an encoding technique, the proposed model returns the relevant devices with a high grade of confidence. After experimentation, the proposed model is validated by comparing it with our current search system, and the results are discussed. The work can potentially impact real-world application scenarios when many different devices are involved.
CEPEDALoCo: An Event-Driven Architecture for Integrating Complex Event Processing and Blockchain through Low-Code (Summary)
Rosa-Bilbao, Jesús; Boubeta-Puig, Juan; Rutle, Adrian. Actas de las XXVIII Jornadas de Ingeniería del Software y Bases de Datos (JISBD 2024), 2024-06-17.
Internet of Things (IoT) is made up of millions of devices generating large amounts of heterogeneous data from multiple sources. These devices can be from multiple manufacturers which makes their use in terms of data acquisition, processing, analysis and actions on these data challenging. Additionally, all these data must be analyzed and correlated in real time for the early detection of situations of interest (complex events) and subsequent decision making. These complex events must be able to automatically trigger decisions and be stored in a secure, immutable and accessible way. In this context, Event-Driven Applications (EDAs) are a solution to meet these needs, however, developing such applications requires vast knowledge in certain technologies. To address these challenges, an EDA is proposed in this paper to integrate Complex Event Processing (CEP) and blockchain through the low-code paradigm. This proposal allows for the development of EDAs in a user-friendly way. These applications make it possible to integrate IoT devices from multiple manufacturers and with different data formats together with CEP technology for complex event detection and blockchain for secure, immutable and accessible event storage. To demonstrate the feasibility, the architecture was applied and evaluated in a case study related to measuring and acting on air quality using IoT devices that measure different pollutants and factors such as temperature, humidity and wind. The results show that the graphically designed EDAs facilitate real-time analysis of the collected IoT data via a CEP engine, whose outcome is transparently and automatically registered in a blockchain network.
Exploring Gender Bias in Remote Pair Programming among Software Engineering Students: The twincode Original Study and First External Replication
Durán, Amador; Fernández, Pablo; Bernárdez, Beatriz; Weinman, Nathaniel; Akalın, Aslıhan; Fox, Armando. Actas de las XXVIII Jornadas de Ingeniería del Software y Bases de Datos (JISBD 2024), 2024-06-17.
Context: Women have historically been underrepresented in Software Engineering, due in part to the stereotyped assumption that women are less technically competent than men. Pair programming is both widely used in industry and has been shown to increase student interest in Software Engineering, particularly among women; but if those same gender biases are also present in pair programming, its potential for attracting women to the field could be thwarted. Objective: We aim to explore the effects of gender bias in pair programming. Specifically, in a remote setting in which students cannot directly observe the gender of their peers, we study whether the perception of the partner, the behavior during programming, or the style of communication of Software Engineering students differ depending on the perceived gender of their remote partner. To our knowledge, this is the first study specifically focusing on the impact of gender stereotypes and bias within pairs in pair programming. Method: We have developed an online pair-programming platform (twincode) that provides a collaborative editing window and a chat pane, both of which are heavily instrumented. Students in the control group had no information about their partner’s gender, whereas students in the treatment group could see a gendered avatar representing the other participant as a man or as a woman. The gender of the avatar was swapped between programming tasks to analyze 45 variables related to the collaborative coding behavior, chat utterances, and questionnaire responses of 46 pairs in the original study at the University of Seville, and 23 pairs in the external replication at the University of California, Berkeley. Results: We did not observe any statistically significant effect of the gender bias treatment, nor any interaction between the perceived partner’s gender and subject’s gender, in any of the 45 response variables measured in the original study. In the external replication, we observed statistically significant effects with moderate to large sizes in four dependent variables within the experimental group, comparing how subjects acted when their partners were represented as a man or a woman. Conclusions: The results in the original study do not show any clear effect of the treatment in remote pair programming among current Software Engineering students. In the external replication, it seems that students delete more source code characters when they have a woman partner, and communicate using more informal utterances, reflections and yes/no questions when they have a man partner, although these results must be considered inconclusive because of the small number of subjects in the replication, and because when multiple test corrections are applied, only the result about informal utterances remains significant. In any case, more mixed methods replications are needed in order to confirm or refute the results in the same and other Software Engineering students populations.
AGORA: Automated Generation of Test Oracles for REST APIs
Alonso Valenzuela, Juan Carlos; Segura, Sergio; Ruiz-Cortés, Antonio. Actas de las XXVIII Jornadas de Ingeniería del Software y Bases de Datos (JISBD 2024), 2024-06-17.
Test case generation tools for REST APIs have grown in number and complexity in recent years. However, their advanced capabilities for automated input generation contrast with the simplicity of their test oracles, which limit the types of failures they can detect to crashes, regressions, and violations of the API specification or design best practices. In this paper, we present AGORA, an approach for the automated generation of test oracles for REST APIs through the detection of invariants—properties of the output that should always hold. In practice, AGORA aims to learn the expected behavior of an API by analyzing previous API requests and their corresponding responses. For this, we extended the Daikon tool for dynamic detection of likely invariants, including the definition of new types of invariants and the implementation of an instrumenter called Beet. Beet converts any OpenAPI specification and a collection of API requests and responses to a format processable by Daikon. As a result, AGORA currently supports the detection of up to 105 different types of invariants in REST APIs. AGORA achieved a total precision of 81.2% when tested on a dataset of 11 operations from 7 industrial APIs. More importantly, the test oracles generated by AGORA detected 6 out of every 10 errors systematically seeded in the outputs of the APIs under test. Additionally, AGORA revealed 11 bugs in APIs with millions of users: Amadeus, GitHub, Marvel, OMDb and YouTube. Our reports have guided developers in improving their APIs, including bug fixes and documentation updates in GitHub. Since it operates in black-box mode, AGORA can be seamlessly integrated into existing API testing tools.