ArtículoThe Dynamic Pipeline ParadigmZoltan, Cristina; Pasarella, Edelmira; Araoz, Julian; Vidal, Maria Esther. Actas de las XIX Jornadas de Programación y Lenguajes (PROLE 2019), 2019-09-02.Nowadays, in the era of Big Data and Internet of Things, large volumes of data in motion are produced in heterogeneous formats, frequencies, densities, and quantities. In general, data is continuously produced by diverse devices and most of them must be processed at real-time. Indeed, this change of paradigm in the way in which data are produced forces us to rethink the way in which they should be processed even in the presence of parallel approaches. To process continuous data, data-driven frameworks are demanded; they are required to dynamically adapt execution schedulers, reconfigure computational structures, and adjust the use of resources according to the characteristics of the input data stream. In previous work, we introduced the Dynamic Pipeline as one of these computational structures and we experimentally showed its efficiency when it is used to solve the problem of counting triangle in a graph. In this work, our aim is to define the main components of the Dynamic Pipeline which is suitable to specify solutions to problems whose incoming data is heterogeneous data in motion. To be concrete, we define the Dynamic Pipeline Paradigm and, additionally, we show the suitability of our framework to specify the solution to different well-known problems. ResumenPitfalls of Jason ConcurrencyFernández Díaz, Álvaro; Benac Earle, Clara; Fredlund, Lars-Ake. Actas de las XIX Jornadas de Programación y Lenguajes (PROLE 2019), 2019-09-02.Jason is a well-known programming language for multia- gent systems where fine-grained concurrency primitives allow a highly- concurrent efficient execution. However, typical concurrency errors such as race conditions are hard to avoid. In this chapter, we analyze a number of such potential pitfalls of the Jason concurrency model, and, describe both how such risks can be mitigated in Jason itself, as well as discussing the alternatives implemented in eJason, an experimental extension of Ja- son with support for distribution and fault tolerance. In some cases, we propose changes in the standard Jason semantics.