21,383 research outputs found

    Detecting Functional Requirements Inconsistencies within Multi-teams Projects Framed into a Model-based Web Methodology

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    One of the most essential processes within the software project life cycle is the REP (Requirements Engineering Process) because it allows specifying the software product requirements. This specification should be as consistent as possible because it allows estimating in a suitable manner the effort required to obtain the final product. REP is complex in itself, but this complexity is greatly increased in big, distributed and heterogeneous projects with multiple analyst teams and high integration between functional modules. This paper presents an approach for the systematic conciliation of functional requirements in big projects dealing with a web model-based approach and how this approach may be implemented in the context of the NDT (Navigational Development Techniques): a web methodology. This paper also describes the empirical evaluation in the CALIPSOneo project by analyzing the improvements obtained with our approach.Ministerio de Economía y Competitividad TIN2013-46928-C3-3-RMinisterio de Economía y Competitividad TIN2015-71938-RED

    Expert System for Crop Disease based on Graph Pattern Matching: A proposal

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    Para la agroindustria, las enfermedades en cultivos constituyen uno de los problemas más frecuentes que generan grandes pérdidas económicas y baja calidad en la producción. Por otro lado, desde las ciencias de la computación, han surgido diferentes herramientas cuya finalidad es mejorar la prevención y el tratamiento de estas enfermedades. En este sentido, investigaciones recientes proponen el desarrollo de sistemas expertos para resolver este problema haciendo uso de técnicas de minería de datos e inteligencia artificial, como inferencia basada en reglas, árboles de decisión, redes bayesianas, entre otras. Además, los grafos pueden ser usados para el almacenamiento de los diferentes tipos de variables que se encuentran presentes en un ambiente de cultivos, permitiendo la aplicación de técnicas de minería de datos en grafos, como el emparejamiento de patrones en los mismos. En este artículo presentamos una visión general de las temáticas mencionadas y una propuesta de un sistema experto para enfermedades en cultivos, basado en emparejamiento de patrones en grafos.For agroindustry, crop diseases constitute one of the most common problems that generate large economic losses and low production quality. On the other hand, from computer science, several tools have emerged in order to improve the prevention and treatment of these diseases. In this sense, recent research proposes the development of expert systems to solve this problem, making use of data mining and artificial intelligence techniques like rule-based inference, decision trees, Bayesian network, among others. Furthermore, graphs can be used for storage of different types of variables that are present in an environment of crops, allowing the application of graph data mining techniques like graph pattern matching. Therefore, in this paper we present an overview of the above issues and a proposal of an expert system for crop disease based on graph pattern matching

    On the Notion of Abstract Platform in MDA Development

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    Although platform-independence is a central property in MDA models, the study of platform-independence has been largely overlooked in MDA. As a consequence, there is a lack of guidelines to select abstraction criteria and modelling concepts for platform-independent design. In addition, there is little methodological support to distinguish between platform-independent and platform-specific concerns, which could be detrimental to the beneficial exploitation of the PIM-PSM separation-of-concerns adopted by MDA. This work is an attempt towards clarifying the notion of platform-independent modelling in MDA development. We argue that each level of platform-independence must be accompanied by the identification of an abstract platform. An abstract platform is determined by the platform characteristics that are relevant for applications at a certain level of platform-independence, and must be established by balancing various design goals. We present some methodological principles for abstract platform design, which forms a basis for defining requirements for design languages intended to support platform-independent design. Since our methodological framework is based on the notion of abstract platform, we pay particular attention to the definition of abstract platforms and the language requirements to specify abstract platforms. We discuss how the concept of abstract platform relates to UML

    A heuristic-based approach to code-smell detection

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    Encapsulation and data hiding are central tenets of the object oriented paradigm. Deciding what data and behaviour to form into a class and where to draw the line between its public and private details can make the difference between a class that is an understandable, flexible and reusable abstraction and one which is not. This decision is a difficult one and may easily result in poor encapsulation which can then have serious implications for a number of system qualities. It is often hard to identify such encapsulation problems within large software systems until they cause a maintenance problem (which is usually too late) and attempting to perform such analysis manually can also be tedious and error prone. Two of the common encapsulation problems that can arise as a consequence of this decomposition process are data classes and god classes. Typically, these two problems occur together – data classes are lacking in functionality that has typically been sucked into an over-complicated and domineering god class. This paper describes the architecture of a tool which automatically detects data and god classes that has been developed as a plug-in for the Eclipse IDE. The technique has been evaluated in a controlled study on two large open source systems which compare the tool results to similar work by Marinescu, who employs a metrics-based approach to detecting such features. The study provides some valuable insights into the strengths and weaknesses of the two approache
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