Revisión del 19:09 9 feb 2018

SBSE Track in JISBD 2018

General information

The Spanish Conference on Software Engineering and Databases (JISBD) is a research forum for researchers from Spain, Portugal and South America working on these fields. The Ibero-American community around these research areas finds in JISBD an annual meeting point where researchers can present, discuss and interchange their research works and ideas, and network. JISBD 2018 is a multi-conference where the IV Track on Search Based Software Engineering (SBSE) will be held.

Location and date: Sevilla, September, 17-19.

Chairs:

Inmaculada Medina Bulo (University of Cádiz)
José Raúl Romero Salguero (University of Córdoba)

Call for papers

Within the Software Engineering field, the appearance of synergies with other areas makes possible the discovery of new ways to solve traditionally complex problems, such as project management, software testing, verification and validation, model driven software engineering, software design, requirements engineering, etc. In this context, the application of search and optimization techniques has lead to the so-called Search Based Software Engineering (SBSE). These automatic techniques provide the engineer with computational solutions that reduce the efforts and human costs required to their resolution.

Another type of algorithm techniques that can be applied to deal with Software Engineering problems is machine learning, a field within Artificial Intelligence that generates solutions based on learning from past experiences. It greatly improves the performance when solving specific problems like learning failure models, requirement extraction, cost prediction, etc. There are also interesting approaches in the context of decision support systems and data mining, whose study deserves further attention. Finally, another research area related with this track is Empirical Software Engineering, which is focused on drawing conclusions from experiments validated by statistical methods.

Fechas importantes

Envío de contribuciones: 4 de marzo
Notificación de aceptación: 22 de abril
Envío de la versión final (camera ready): 13 de mayo
Celebración del congreso: 17 al 19 de septiembre

@@ Línea 18: / Línea 18: @@
 Within the Software Engineering field, the appearance of synergies with other areas makes possible the discovery of new ways to solve traditionally complex problems, such as project management, software testing, verification and validation, model driven software engineering, software design, requirements engineering, etc. In this context, the application of search and optimization techniques has lead to the so-called Search Based Software Engineering (SBSE). These automatic techniques provide the engineer with computational solutions that reduce the efforts and human costs required to their resolution.
-Otra fuente de t&eacute;cnicas algor&iacute;tmicas para resolver problemas de Ingenier&iacute;a del Software es el aprendizaje autom&aacute;tico, una disciplina de la inteligencia artificial que genera soluciones basadas en el aprendizaje a partir de la experiencia y que mejoran notablemente el rendimiento a la hora de resolver determinados problemas, como el aprendizaje de modelos de fallos, la extracci&oacute;n de requisitos, la predicci&oacute;n de costes, etc. En el contexto del apoyo a la decisi&oacute;n y la miner&iacute;a de datos tambi&eacute;n se proponen soluciones interesantes para el ingeniero software cuyo estudio merece ser destacado. Finalmente, adem&acute;s de las anteriores, otra &aacute;rea fuertemente vinculada y que tiene especial cabida en este track es la Ingenier&iacute;a del Software Emp&iacute;rica, centrada en extraer conclusiones a partir de experimentos validados con m&eacute;todos estad&iacute;sticos.
+Another type of algorithm techniques that can be applied to deal with Software Engineering problems is machine learning, a field within Artificial Intelligence that generates solutions based on learning from past experiences. It greatly improves the performance when solving specific problems like learning failure models, requirement extraction, cost prediction, etc. There are also interesting approaches in the context of decision support systems and data mining, whose study deserves further attention. Finally, another research area related with this track is Empirical Software Engineering, which is focused on drawing conclusions from experiments validated by statistical methods.
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