An overview of the ciao multiparadigm language and program development environment and its design philosophy

We describe some of the novel aspects and motivations behind the design and implementation of the Ciao multiparadigm programming system. An important aspect of Ciao is that it provides the programmer with a large number of useful features from different programming paradigms and styles, and that the use of each of these features can be turned on and off at will for each program module. Thus, a given module may be using e.g. higher order functions and constraints, while another module may be using objects, predicates, and concurrency. Furthermore, the language is designed to be extensible in a simple and modular way. Another important aspect of Ciao is its programming environment, which provides a powerful preprocessor (with an associated assertion language) capable of statically finding non-trivial bugs, verifying that programs comply with specifications, and performing many types of program optimizations. Such optimizations produce code that is highly competitive with other dynamic languages or, when the highest levéis of optimization are used, even that of static languages, all while retaining the interactive development environment of a dynamic language. The environment also includes a powerful auto-documenter. The paper provides an informal overview of the language and program development environment. It aims at illustrating the design philosophy rather than at being exhaustive, which would be impossible in the format of a paper, pointing instead to the existing literature on the system.

An overview of ciao and its design philosophy

We provide an overall description of the Ciao multiparadigm programming system emphasizing some of the novel aspects and motivations behind its design and implementation. An important aspect of Ciao is that, in addition to supporting logic programming (and, in particular, Prolog), it provides the programmer with a large number of useful features from different programming paradigms and styles and that the use of each of these features (including those of Prolog) can be turned on and off at will for each program module. Thus, a given module may be using, e.g., higher order functions and constraints, while another module may be using assignment, predicates, Prolog meta-programming, and concurrency. Furthermore, the language is designed to be extensible in a simple and modular way. Another important aspect of Ciao is its programming environment, which provides a powerful preprocessor (with an associated assertion language) capable of statically finding non-trivial bugs, verifying that programs comply with specifications, and performing many types of optimizations (including automatic parallelization). Such optimizations produce code that is highly competitive with other dynamic languages or, with the (experimental) optimizing compiler, even that of static languages, all while retaining the flexibility and interactive development of a dynamic language. This compilation architecture supports modularity and separate compilation throughout. The environment also includes a powerful autodocumenter and a unit testing framework, both closely integrated with the assertion system. The paper provides an informal overview of the language and program development environment. It aims at illustrating the design philosophy rather than at being exhaustive, which would be impossible in a single journal paper, pointing instead to previous Ciao literature.

Interactividad programada en el Game Engine de Blender

Con este proyecto se ha desarrollado una guía introductoria a uno de los aspectos más complejos y especializados de Blender, que es el control de su motor de videojuegos mediante programas escritos en Python. Está orientado a lectores que tienen un conocimiento amplio sobre el manejo de Blender, su interfaz y el funcionamiento de sus diferentes elementos, así como una mínima experiencia en cuanto a programación. Se ha organizado en una parte descriptiva, centrada en el lenguaje Python y en las bases de su uso para programar el motor de videojuegos (Game Engine) de Blender, y otra de práctica guiada, que constituye la mayoría del proyecto, donde se estudian de manera progresiva ejemplos concretos de uso del mismo. En la parte descriptiva se ha tratado tanto el funcionamiento más básico del lenguaje Python, especialmente las características que difieren de otros lenguajes de programación tradicionales, como su relación con Blender en particular, explicando las diferentes partes de la API de Blender para Python, y las posibles estrategias de uso. La parte práctica guiada, dado que esta interacción entre Blender y Python ofrece un rango de posibilidades muy amplio, se ha centrado en tres áreas concretas que han sido investigadas en profundidad: el control del objeto protagonista, de la cámara y la implementación de un mapa de orientación. Todas ellas se han centrado en torno a un ejemplo común, que consiste en un videojuego muy básico, y que, gracias a los ficheros de Blender que acompañan a esta memoria, sirve para apoyar las explicaciones y poder probar su efecto directamente. Por una parte, estos tres aspectos prácticos se han explicado exhaustivamente, y se han llevado hasta un nivel relativamente alto. Asimismo se han intentado minimizar las dependencias, tanto entre ellos como con la escena que se ha usado como ejemplo, de manera que sea sencillo usar los programas generados en otras aplicaciones. Por otra, la mayoría de los problemas que ha sido necesario resolver durante el desarrollo no son específicos de ninguna de las tres áreas, sino que son de carácter general, por lo que sus explicaciones podrán usarse al afrontar otras situaciones. ABSTRACT. This Thesis consists of an introductory guide to one of the most complex and specific parts of Blender, which is the control of its game engine by means of programs coded in Python. The dissertation is orientated towards readers who have a good knowledge of Blender, its interface and how its different systems work, as well as basic programming skills. The document is composed of two main sections, the first one containing a description of Python’s basics and its usage within Blender, and the second consisting of three practical examples of interaction between them, guided and explained step by step. On the first section, the fundamentals of Python have been covered in the first place, focusing on the characteristics that distinguish it from other programming languages. Then, Blender’s API for Python has also been introduced, explaining its different parts and the ways it can be used in. Since the interaction between Blender and Python offers a wide range of possibilities, the practical section has been centered on three particular areas. Each one of the following sections has been deeply covered: how to control the main character object, how to control the camera, and how to implement and control a mini-map. Furthermore, a demonstrative videogame has been generated for the reader to be able to directly test the effect of what is explained in each section. On the one hand, these three practical topics have been thoroughly explained, starting from the basis and gradually taking them to a relatively advanced level. The dependences among them, or between them and the demonstrative videogame, have been minimised so that the scripts or ideas can be easily used within other applications. On the other hand, most of the problems that have been addressed are not exclusively related to these areas, but will most likely appear in different situations, thus enlarging the field in which this Thesis can be used.

Essentials in Ontology Engineering: Methodologies, Languages, and Tools

In the beginning of the 90s, ontology development was similar to an art: ontology developers did not have clear guidelines on how to build ontologies but only some design criteria to be followed. Work on principles, methods and methodologies, together with supporting technologies and languages, made ontology development become an engineering discipline, the so-called Ontology Engineering. Ontology Engineering refers to the set of activities that concern the ontology development process and the ontology life cycle, the methods and methodologies for building ontologies, and the tool suites and languages that support them. Thanks to the work done in the Ontology Engineering field, the development of ontologies within and between teams has increased and improved, as well as the possibility of reusing ontologies in other developments and in final applications. Currently, ontologies are widely used in (a) Knowledge Engineering, Artificial Intelligence and Computer Science, (b) applications related to knowledge management, natural language processing, e-commerce, intelligent information integration, information retrieval, database design and integration, bio-informatics, education, and (c) the Semantic Web, the Semantic Grid, and the Linked Data initiative. In this paper, we provide an overview of Ontology Engineering, mentioning the most outstanding and used methodologies, languages, and tools for building ontologies. In addition, we include some words on how all these elements can be used in the Linked Data initiative.

Modular extensions for modular (Logic) languages

We address the problem of developing mechanisms for easily implementing modular extensions to modular (logic) languages. By(language) extensions we refer to different groups of syntactic definitions and translation rules that extend a language. Our use of the concept of modularity in this context is twofold. We would like these extensions to be modular, in the sense above, i.e., we should be able to develop different extensions mostly separately. At the same time, the sources and targets for the extensions are modular languages, i.e., such extensions may take as input sepárate pieces of code and also produce sepárate pieces of code. Dealing with this double requirement involves interesting challenges to ensure that modularity is not broken: first, combinations of extensions (as if they were a single extensión) must be given a precise meaning. Also, the sepárate translation of múltiple sources (as if they were a single source) must be feasible. We present a detailed description of a code expansion-based framework that proposes novel solutions for these problems. We argüe that the approach, while implemented for Ciao, can be adapted for other Prolog-based systems and languages.

Independence and search space preservation in dynamically scheduled constraint logic languages

This paper performs a further generalization of the notion of independence in constraint logic programs to the context of constraint logic programs with dynamic scheduling. The complexity of this new environment made necessary to first formally define the relationship between independence and search space preservation in the context of CLP languages. In particular, we show that search space preservation is, in the context of CLP languages, not only a sufficient but also a necessary condition for ensuring that both the intended solutions and the number of transitions performed do not change. These results are then extended to dynamically scheduled languages and used as the basis for the extension of the concepts of independence. We also propose several a priori sufficient conditions for independence and also give correctness and efficiency results for parallel execution of constraint logic programs based on the proposed notions of independence.

Impact damage on selected varieties of apples, pears and other fruits.

During the past years, different laboratory impact response studies have been carrj.ec out in following fruits: apples (2 varieties), pears (4 varieties), Asian or Nashi pears (4 varieties), melons (2 varieties), peaches (2 varieties) and avocados. The methodology of the tests is described, as well as the results and observations obtained in each group of tests. Impact response is compared to bruising susceptibility, bruise characteristics (appearance and structural features) and varietal and ripeness differences.