Combining Languages and Techniques

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https://hdl.handle.net/11705/PROLE/2015/CLT
Artículos en la categoría Combining Languages and Techniques publicados en las Actas de las XV Jornadas de Programación y Lenguajes (PROLE 2015).
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    Artículo
    Constraint Programming Meets SQL
    Caballero, Rafael; Ieva, Carlo. Actas de las XV Jornadas de Programación y Lenguajes (PROLE 2015), 2015-09-15.
    We present a proposal for introducing SQL tuples into the modeling programming language MINIZINC. The domain of the new decision variables is defined by arbitrary relational database tables indicated by the user. The new setting increases the expressiveness of MINIZINC, allowing the modeler to mix the usual finite domains already existing in the language with string constraints typical from SQL such as concat, substr, or like. In order to obtain the solutions of these combined models, we first replace the atomic constraints involving strings by boolean variables. The result is a standard MINIZINC model, which can be solved by any off-the-shelf solver. Then, each individual solution is applied to the remainder string constraints, which are then solved using an SQL query. We discuss how both languages, MINIZINC and SQL, benefit from this combination.
  • Miniatura
    Artículo
    Analysing the Termination of Term Rewriting Systems using Data Mining
    Piris, J.; Fabregat, H.; Ramírez-Quintana, M. J.. Actas de las XV Jornadas de Programación y Lenguajes (PROLE 2015), 2015-09-15.
    During the last decades, researchers in the field of Term Rewriting System (TRS) have devoted a lot of effort in order to develop techniques and methods able to demonstrate the termination property of a TRS. As a consequence, some of the proposed techniques have been implemented and several termination tools have been developed in order to automatize the termination proofs. From 2004, the annual Termination Competition is the foro in which research groups compare their tools trying to provide termination proofs of as many TRS as possible. This event generates a large amount of information (results obtained by the different tools, time spent on each proof, ...) that is recorded in databases. In this paper, we propose an alternative approach to study the termination of TRS: to use data mining techniques that, based on the historical information collected in the competition, generate models to explore the termination of a TRS. The goal of our study is not to develop a termination tool but to show, for the first time, what machine learning techniques can offer to the analysis of TRS termination.