The use of the Python programming language for scientific computing has been gaining momentum in the last years. The fact that it is compact and readable and its complete set of scientific libraries are two important characteristics that favour its adoption. Nevertheless, Python still lacks a solution for easily parallelising generic scripts on distributed infrastructures, since the current alternatives mostly require the use of APIs for message passing or are restricted to embarrassingly-parallel computations.In that sense, this paper presents PyCOMPSs, a framework that facilitates the development of parallel computational workflows in Python. In this approach, the user programs her script in a sequential fashion and decorates the functions to be run as asynchronous parallel tasks. A runtime system is in charge of exploiting the inherent concurrency of the script, detecting the data dependencies between tasks and spawning them to the available resources.Furthermore, we show how this programming model can be built on top of a big data storage architecture, where the data stored in the backend is abstracted and

To ensure the quality of an information system, it is essential that the conceptual schema that represents the knowledge about its domain is semantically correct. The semantic correctness of a conceptual schema can be seen from two different perspectives. On the one hand, from the point of view of its definition, a conceptual schema must be right. This is ensured by means of verification techniques that check whether the schema satisfies several correctness properties. On the other hand, from the point of view of the requirements that the information system should satisfy, a schema must also be the right one. This is ensured by means of validation techniques, which help the designer understand the exact meaning of a schema and to see whether it corresponds to the requirements. In this article we propose an approach to verify and validate UML conceptual schemas, with arbitrary constraints formalized in OCL. We have also implemented our approach to show its feasibility.

Abstract. We propose a new approach to check whether a given UML class diagram with its OCL integrity constraints satisfies a set of desirable properties such as schema satisfiability, class liveliness, redundancy of integrity constraints or reachability of partially specified states. Our approach is based on translating both the class diagram and the OCL constraints into a logic representation. Then, we use the CQC Method to verify whether these properties hold for the given diagram and constraints.

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A conceptual schema specifies the relevant information about the domain and how this information changes as a result of the execution of operations. The purpose of reasoning on a conceptual schema is to check whether the conceptual schema is correctly specified. This task is not fully formalizable, so it is desirable to provide the designer with tools that assist him or her in the validation process. To this end, we present a method to translate a conceptual schema with operations into logic, and then propose a set of validation tests that allow assessing the (un)correctness of the schema. These tests are formulated in such a way that a generic reasoning method can be used to check them. To show the feasibility of our approach, we use an implementation of an existing reasoning method.