http://sedici.unlp.edu.ar:80/handle/10915/134662 2026-03-11T01:43:58Z 2026-03-11T01:43:58Z Gramajo, María Guadalupe Ballejos, Luciana C. Ale, Mariel Alejandra http://sedici.unlp.edu.ar:80/handle/10915/135042 2022-04-26T20:03:21Z 2019-07-05T00:00:00Z

Articulo Electronic Journal of SADIO; vol. 18, no. 1 In agile software development projects, user stories are written in natural language in order to describe the functionalities and features requested by interested parties. Given the ambiguous nature of natural language, user stories may reflect feelings intrinsically expressed by the product owner during requirements education tasks. While their visualization and identification are complex, word processing and sentiment analysis techniques can be applied to extract useful and valuable information for the development team. For that reason, this paper proposes a methodology to analyze the affective dimension of user stories, considering the feelings and emotions that affect the communication process amongteam members and identify how these factors impact the software development process, specifically in activities related to the definition and specification of requirements. Special Issue dedicated to JAIIO 2018 (Jornadas Argentinas de Informática).

2019-07-05T00:00:00Z In agile software development projects, user stories are written in natural language in order to describe the functionalities and features requested by interested parties. Given the ambiguous nature of natural language, user stories may reflect feelings intrinsically expressed by the product owner during requirements education tasks. While their visualization and identification are complex, word processing and sentiment analysis techniques can be applied to extract useful and valuable information for the development team. For that reason, this paper proposes a methodology to analyze the affective dimension of user stories, considering the feelings and emotions that affect the communication process amongteam members and identify how these factors impact the software development process, specifically in activities related to the definition and specification of requirements. Duboue, Pablo Ariel http://sedici.unlp.edu.ar:80/handle/10915/135041 2022-04-26T20:03:22Z 2019-07-05T00:00:00Z

Articulo Electronic Journal of SADIO; vol. 18, no. 1; http://sedici.unlp.edu.ar/handle/10915/70714 We are interested in data-driven approaches to Natural Language Generation, but semantic representations for human text are difficult and expensive to construct. By considering a methods implementation as weak semantics for the English terms extracted from the method’s name we can collect massive datasets, akin to have words and sensor dataaligned at a scale never seen before. We applied our learned model to name scrambling, a common technique used to protect intellectual property and increase the effort necessary to reverse engineer Java binary code: replacing all the method and class names by a random identifier. Using 5.6M bytecode-compiled Java methods obtained from the Debianarchive, we trained a Random Forest model to predict the first term in the method name. As features, we use primarily the opcodes of the bytecodes (that is, bytecodes without any parameters). Our results indicate that we can distinguish the 15 most popular terms from the others at 78% recall, helping a programmer performing reverse engineering to reduce half of the methods in a program they should further investigate. We also performed some preliminary experiments using neural machine translation. Special Issue dedicated to JAIIO 2018 (Jornadas Argentinas de Informática).

2019-07-05T00:00:00Z We are interested in data-driven approaches to Natural Language Generation, but semantic representations for human text are difficult and expensive to construct. By considering a methods implementation as weak semantics for the English terms extracted from the method’s name we can collect massive datasets, akin to have words and sensor dataaligned at a scale never seen before. We applied our learned model to name scrambling, a common technique used to protect intellectual property and increase the effort necessary to reverse engineer Java binary code: replacing all the method and class names by a random identifier. Using 5.6M bytecode-compiled Java methods obtained from the Debianarchive, we trained a Random Forest model to predict the first term in the method name. As features, we use primarily the opcodes of the bytecodes (that is, bytecodes without any parameters). Our results indicate that we can distinguish the 15 most popular terms from the others at 78% recall, helping a programmer performing reverse engineering to reduce half of the methods in a program they should further investigate. We also performed some preliminary experiments using neural machine translation. Pinto, Noelia Soledad Tortosa, Nicolás Cabas Geat, Blas Ibáñez, Lucas Acuña, César J. http://sedici.unlp.edu.ar:80/handle/10915/135040 2022-04-26T20:03:23Z 2019-07-05T00:00:00Z

Articulo Validation of the reengineering applied on the first version of Agile Quality Framework Electronic Journal of SADIO; vol. 18, no. 1 Actualmente las empresas de Software, para mantener la competitividad en el escenario mundial, deben ofrecer productos y servicios de calidad a través de la implementación de modelos y normas reconocidas internacionalmente. Sin embargo, esto no es posible en las Pequeñas y Medianas Empresas (PYMES) debido a los altos costos de implementación, escases de personal especializado y tiempos acotados. Además, en el Nordeste Argentino (NEA), las PYMES, han iniciado la aplicación de prácticas ágiles de desarrollo de software que se contraponen a formalizaciones exigidas por los procesos de certificación de calidad más usados actualmente. Por tal motivo se ha desarrollado AQF, un framework que integra un modelo de calidad junto a una herramienta de software para la evaluación de calidad en entornos ágiles. Debido a que se obtuvieron resultados de validaciones previas, en este artículo se presenta AQF 2.0 con nuevas características y mejoras adecuadas a la realidad de la Industria del Software en el NEA, incluyendo detalles del proceso de evaluación que utiliza AQF respecto a la Gestión de Requerimientos y Requisitos en proyectos ágiles.; Currently, the software industry requires high quality products and services, which is achieved through the application of internationally recognized quality models and methods. However, these models in SMEs are very difficultto implement because it require a large investment in money, time and resources. With the aim of facilitating the adoption of practices that ensure quality, we have implemented a framework that integrates a quality model together with the toolthat implements it, AQF. AQF allows the evaluation of quality in agile environments, considering as the object of the measurement to the development process independently of the selected agile focus. After the results obtained in previous validations, this article presents AQF 2.0 with new features and improvements adapted to NEA Software Industry reality,including evaluation process details by AQF regarding the Requirements Management in agile projects. Special Issue dedicated to JAIIO 2018 (Jornadas Argentinas de Informática).

2019-07-05T00:00:00Z Actualmente las empresas de Software, para mantener la competitividad en el escenario mundial, deben ofrecer productos y servicios de calidad a través de la implementación de modelos y normas reconocidas internacionalmente. Sin embargo, esto no es posible en las Pequeñas y Medianas Empresas (PYMES) debido a los altos costos de implementación, escases de personal especializado y tiempos acotados. Además, en el Nordeste Argentino (NEA), las PYMES, han iniciado la aplicación de prácticas ágiles de desarrollo de software que se contraponen a formalizaciones exigidas por los procesos de certificación de calidad más usados actualmente. Por tal motivo se ha desarrollado AQF, un framework que integra un modelo de calidad junto a una herramienta de software para la evaluación de calidad en entornos ágiles. Debido a que se obtuvieron resultados de validaciones previas, en este artículo se presenta AQF 2.0 con nuevas características y mejoras adecuadas a la realidad de la Industria del Software en el NEA, incluyendo detalles del proceso de evaluación que utiliza AQF respecto a la Gestión de Requerimientos y Requisitos en proyectos ágiles. Currently, the software industry requires high quality products and services, which is achieved through the application of internationally recognized quality models and methods. However, these models in SMEs are very difficultto implement because it require a large investment in money, time and resources. With the aim of facilitating the adoption of practices that ensure quality, we have implemented a framework that integrates a quality model together with the toolthat implements it, AQF. AQF allows the evaluation of quality in agile environments, considering as the object of the measurement to the development process independently of the selected agile focus. After the results obtained in previous validations, this article presents AQF 2.0 with new features and improvements adapted to NEA Software Industry reality,including evaluation process details by AQF regarding the Requirements Management in agile projects. Giordano, Andrés Banchero, Santiago Cerny, Natacha De Marzi, Mauricio Tolosa, Gabriel Hernán http://sedici.unlp.edu.ar:80/handle/10915/135039 2022-04-26T20:03:24Z 2019-07-05T00:00:00Z

Articulo Electronic Journal of SADIO; vol. 18, no. 1 Social Networks have shown great growth relating the number of their users and generated content. For example, Twitter is used as a means to gather support, express ideas and opinions on various topics or interact with users with similar interests. In the latter case, the idea of community formation appears, that is, groups of users that are moreclosely related to each other than the rest of the nodes in the network. In this work we propose the detection of the community of users of Argentina interested in the celiac disease. We apply a series of techniques to detect and characterize them. In addition, we propose and use a methodology for the detection of more influential and active nodes(users), showing how the community can be reinforced by the recommendation of some particular links. The results show that with only a low percentage of accepted recommendation the network becomes denser and average distance between two users decreases quickly, thus improving the spread of information. Special Issue dedicated to JAIIO 2018 (Jornadas Argentinas de Informática).

2019-07-05T00:00:00Z Social Networks have shown great growth relating the number of their users and generated content. For example, Twitter is used as a means to gather support, express ideas and opinions on various topics or interact with users with similar interests. In the latter case, the idea of community formation appears, that is, groups of users that are moreclosely related to each other than the rest of the nodes in the network. In this work we propose the detection of the community of users of Argentina interested in the celiac disease. We apply a series of techniques to detect and characterize them. In addition, we propose and use a methodology for the detection of more influential and active nodes(users), showing how the community can be reinforced by the recommendation of some particular links. The results show that with only a low percentage of accepted recommendation the network becomes denser and average distance between two users decreases quickly, thus improving the spread of information. Pons, Claudia Fabiana Garrido, Alejandra http://sedici.unlp.edu.ar:80/handle/10915/135038 2022-04-26T20:03:24Z 2019-07-05T00:00:00Z

Contribucion a revista Editorial Note by Claudia Pons and Alejandra Garrido Electronic Journal of SADIO; vol. 18, no. 1 This edition of the EJS contains the extended versions of a set of articles that were selected among those presented at 47 JAIIO, Argentine Conference on Information Technology. Special Issue dedicated to JAIIO 2018 (Jornadas Argentinas de Informática).

2019-07-05T00:00:00Z This edition of the EJS contains the extended versions of a set of articles that were selected among those presented at 47 JAIIO, Argentine Conference on Information Technology. Amorim, Natalia de Vargas, Rogério R. de Galafassi, Cristiano Russini, Alexandre http://sedici.unlp.edu.ar:80/handle/10915/135037 2022-04-26T20:03:26Z 2019-07-05T00:00:00Z

Articulo Electronic Journal of SADIO; vol. 18, no. 1 Technology has provided efficiency and practicality for daily routines of people and companies. The market has solutions to flexibilize access that usually uses hard security controls which needs constant actions from a manager. This way, the paper aims to formalize a control access model that uses artificial intelligence techniques to adapt itself to the users behavior changes. Still, we present a case study of the implementation of this model. It was verified that the model presented satisfactory performance and it is suggested, as future works, the use of neural networks to make a comparison with this work. Special Issue dedicated to JAIIO 2018 (Jornadas Argentinas de Informática).

2019-07-05T00:00:00Z Technology has provided efficiency and practicality for daily routines of people and companies. The market has solutions to flexibilize access that usually uses hard security controls which needs constant actions from a manager. This way, the paper aims to formalize a control access model that uses artificial intelligence techniques to adapt itself to the users behavior changes. Still, we present a case study of the implementation of this model. It was verified that the model presented satisfactory performance and it is suggested, as future works, the use of neural networks to make a comparison with this work. Palazzo, Martin Beauseroy, Pierre Yankilevich, Patricio http://sedici.unlp.edu.ar:80/handle/10915/135036 2022-04-26T20:03:27Z 2019-07-01T00:00:00Z

Articulo Electronic Journal of SADIO; vol. 18, no. 1 Cancer researchers are facing the opportunity to analyze and learn from big quantities of omic profiles of tumor samples. Different omic data is now available in several databases and the bioinformatics data analysis and interpretation are current bottlenecks. In this study somatic mutations and gene expression data from Hepatocellular carcinoma tumor samples are used to discriminate by Kernel Learning between tumor subtypes and early and late stages. This classification will allow medical doctors to establish an appropriate treatment according to the tumor stage. By building kernel machines we could discriminate both classes with an acceptable classification accuracy. Feature selection have been implemented to select the key genes which differential expression improves the separability between the samples of early and late stages. Special Issue dedicated to JAIIO 2018 (Jornadas Argentinas de Informática).

2019-07-01T00:00:00Z Cancer researchers are facing the opportunity to analyze and learn from big quantities of omic profiles of tumor samples. Different omic data is now available in several databases and the bioinformatics data analysis and interpretation are current bottlenecks. In this study somatic mutations and gene expression data from Hepatocellular carcinoma tumor samples are used to discriminate by Kernel Learning between tumor subtypes and early and late stages. This classification will allow medical doctors to establish an appropriate treatment according to the tumor stage. By building kernel machines we could discriminate both classes with an acceptable classification accuracy. Feature selection have been implemented to select the key genes which differential expression improves the separability between the samples of early and late stages.