El presente artículo aborda las interrogantes presentes en México a partir del sur-gimiento del enfoque de la justicia transicional, poniendo especial atención en elimpacto de la construcción democrática visto a la luz de la historiografía y con los de-rechos humanos como perspectiva. El argumento se centra en plantear que, en Méxicoaparece la justicia transicional como resultado de un contexto en el que convergen unsistema de alta y persistente violencia, junto a un legado de violaciones a los derechoshumanos de la historia reciente, ante lo cual, diversos sectores hacen un llamado a quese atienda esta situación, ya que de no hacerlo, se compromete el Estado Democráticode Derecho. Desde esta perspectiva se revisa la historia reciente del país y los derechoshumanos, las narrativas y ejercicios del tema como objeto de estudio, vistos desde lamovilización e incidencia y el Estado mismo.
This article proposes the Coding Ants framework, an approach for auto-tuning which uses ant colony optimization to find a sequence of code optimizations for GPU architectures. The proposed framework is built as an extension to the PPCG compiler, a source-to-source code generator based on the polyhedral model and specializing in the generation of CUDA code. As such, the Coding Ants framework is able to use the polyhedral abstraction to represent a large space of possible transformations. Several optimizations are also presented which have not been included in any previous GPU auto-tuning system. The proposed framework also extends the traditional ant colony optimization algorithm to include performance metrics as well as a regression tree analysis to segment the search space. We evaluate the framework on the PolyBench suite and compare the performance of three levels of optimization that transfer increasing control to the Coding Ants framework from the PPCG cost model. (C) 2018 Elsevier Ltd. All rights reserved.
Most existing software reliability growth models (SGRMs) often assume software faults are mutually independent and the detected faults can be perfectly removed. However, those two assumptions are not realistic in practice since the dependent faults can also exist in the program. At the same time, it is unlikely to correct all the detected faults in the testing phase due to the limitation of testing resource, the skill and experience of the programmer, and multi-release consideration for software organization. This paper presents a new nonhomogeneous Poisson process (NHPP) software reliability model with a pioneering idea by considering software fault dependency and imperfect fault removal. In order to clearly explain software fault dependency, some facts and examples are discussed in Section 1. Two types of software faults are defined, Type I (independent) fault and Type II (dependent) fault, according to fault dependency. Two phases debugging processes, Phase I and Phase II, are proposed according to the debugged software fault type. A small portion of software faults that software testers are not able to remove is also considered in both phases in the proposed model. The illustration of the model effectiveness is based on the three datasets collected from industries. Some limitations of the proposed model are also discussed in the last section. (C) 2017 Elsevier Ltd. All rights reserved.
Usually, Aspect-Oriented Programming (AOP) languages are an extension of a specific target programming language (e.g., AspectJ for Java and AspectC++ for C++). Although providing AOP support with target language extensions may ease the adoption of an approach, it may impose constraints related with constructs and semantics. Furthermore, by tightly coupling the AOP language to the target language the reuse potential of many aspects, especially the ones regarding non-functional requirements, is lost. LARA is a domain-specific language inspired by AOP concepts, having the specification of source-to-source transformations as one of its main goals. LARA has been designed to be, as much as possible, independent of the target language and to provide constructs and semantics that ease the definition of concerns, especially related to non-functional requirements. In this paper, we propose techniques to overcome some of the challenges presented by a multilanguage approach to AOP of cross-cutting concerns focused on non-functional requirements and applied through the use of a weaving process. The techniques mainly focus on providing well-defined library interfaces that can have concrete implementations for each supported target language. The developer uses an agnostic interface and the weaver provides a specific implementation for the target language. We evaluate our approach using 8 concerns with varying levels of language agnosticism that support 4 target languages (C, C++, Java and MATLAB) and show that the proposed techniques contribute to more concise LARA aspects, high reuse of aspects, and to significant effort reductions when developing weavers for new imperative, object-oriented programming languages.
