How Evolutionary Visual Software Analytics Supports Knowledge Discovery

[EN] Evolutionary visual software analytics is a specialization of visual analytics. It is aimed at supporting software maintenance processes by aiding the understanding and comprehension of software evolution with the active participation of users. Therefore, it deals with the analysis of software projects that have been under development and maintenance for several years and which are usually formed by thousands of software artifacts,which are also associated to logs from communications, defect-tracking and software configuration management systems. Accordingly, evolutionary visual software analytics aims to assist software developers and software project managers by means of an integral approach that takes into account knowledge extraction techniques as well as visual representations that make use of interaction techniques and linked views. Consequently,this paper discusses the implementation of an architecture based on the evolutionary visual software analytics process and how it supports knowledge discovery during software maintenance tasks.[ES] Analítica de software visual evolutivos es una especialización de la analítica visual. Está dirigido a apoyar los procesos de mantenimiento de software, ayudando al entendimiento y la comprensión de la evolución del software, con la participación activa de los usuarios. Por lo tanto, tiene que ver con el análisis de los proyectos de software que han estado bajo desarrollo y mantenimiento por varios años y que por lo general están formados por miles de artefactos de software, que también están asociadas a los registros de las comunicaciones, seguimiento de defectos y sistemas de gestión de configuración de software. En consecuencia, la analítica de software visual evolutivos tiene como objetivo ayudar a los desarrolladores de software y administradores de proyectos de software a través de un enfoque integral que tenga en cuenta las técnicas de extracción de conocimiento, así como representaciones visuales que hacen uso de técnicas de interacción y vistas enlazadas. En consecuencia, en este documento se analiza la implementación de una arquitectura basada en el proceso de analítica de software visual evolutivos y la forma en que apoya el descubrimiento de conocimiento durante las tareas de mantenimiento de softwar

Design Features for the Social Web: The Architecture of Deme

We characterize the "social Web" and argue for several features that are desirable for users of socially oriented web applications. We describe the architecture of Deme, a web content management system (WCMS) and extensible framework, and show how it implements these desired features. We then compare Deme on our desiderata with other web technologies: traditional HTML, previous open source WCMSs (illustrated by Drupal), commercial Web 2.0 applications, and open-source, object-oriented web application frameworks. The analysis suggests that a WCMS can be well suited to building social websites if it makes more of the features of object-oriented programming, such as polymorphism, and class inheritance, available to non-programmers in an accessible vocabulary.Comment: Appeared in Luis Olsina, Oscar Pastor, Daniel Schwabe, Gustavo Rossi, and Marco Winckler (Editors), Proceedings of the 8th International Workshop on Web-Oriented Software Technologies (IWWOST 2009), CEUR Workshop Proceedings, Volume 493, August 2009, pp. 40-51; 12 pages, 2 figures, 1 tabl

Res2Net: A New Multi-scale Backbone Architecture

Representing features at multiple scales is of great importance for numerous vision tasks. Recent advances in backbone convolutional neural networks (CNNs) continually demonstrate stronger multi-scale representation ability, leading to consistent performance gains on a wide range of applications. However, most existing methods represent the multi-scale features in a layer-wise manner. In this paper, we propose a novel building block for CNNs, namely Res2Net, by constructing hierarchical residual-like connections within one single residual block. The Res2Net represents multi-scale features at a granular level and increases the range of receptive fields for each network layer. The proposed Res2Net block can be plugged into the state-of-the-art backbone CNN models, e.g., ResNet, ResNeXt, and DLA. We evaluate the Res2Net block on all these models and demonstrate consistent performance gains over baseline models on widely-used datasets, e.g., CIFAR-100 and ImageNet. Further ablation studies and experimental results on representative computer vision tasks, i.e., object detection, class activation mapping, and salient object detection, further verify the superiority of the Res2Net over the state-of-the-art baseline methods. The source code and trained models are available on https://mmcheng.net/res2net/.Comment: 11 pages, 7 figure

Towards a re-engineering method for web services architectures

Recent developments in Web technologies – in particular through the Web services framework – have greatly enhanced the flexible and interoperable implementation of service-oriented software architectures. Many older Web-based and other distributed software systems will be re-engineered to a Web services-oriented platform. Using an advanced e-learning system as our case study, we investigate central aspects of a re-engineering approach for the Web services platform. Since our aim is to provide components of the legacy system also as services in the new platform, re-engineering to suit the new development paradigm is as important as re-engineering to suit the new architectural requirements

Encoding of Intention and Spatial Location in the Posterior Parietal Cortex

The posterior parietal cortex is functionally situated between sensory cortex and motor cortex. The responses of cells in this area are difficult to classify as strictly sensory or motor, since many have both sensory- and movement-related activities, as well as activities related to higher cognitive functions such as attention and intention. In this review we will provide evidence that the posterior parietal cortex is an interface between sensory and motor structures and performs various functions important for sensory-motor integration. The review will focus on two specific sensory-motor tasks-the formation of motor plans and the abstract representation of space. Cells in the lateral intraparietal area, a subdivision of the parietal cortex, have activity related to eye movements the animal intends to make. This finding represents the lowest stage in the sensory-motor cortical pathway in which activity related to intention has been found and may represent the cortical stage in which sensory signals go "over the hump" to become intentions and plans to make movements. The second part of the review will discuss the representation of space in the posterior parietal cortex. Encoding spatial locations is an essential step in sensory-motor transformations. Since movements are made to locations in space, these locations should be coded invariant of eye and head position or the sensory modality signaling the target for a movement Data will be reviewed demonstrating that there exists in the posterior parietal cortex an abstract representation of space that is constructed from the integration of visual, auditory, vestibular, eye position, and propriocaptive head position signals. This representation is in the form of a population code and the above signals are not combined in a haphazard fashion. Rather, they are brought together using a specific operation to form "planar gain fields" that are the common foundation of the population code for the neural construct of space