SEED is a software tool designed for Java consisting of a class library and a set of simulators to facilitate learning of the main data structures. The educational component is based on an active case‐solving methodology accompanied by a pedagogical strategy. This strategy allows for the development of a multilayer‐model‐programming work for the construction of basic and advanced applications in real domains and for integration of its use, development and operation assessment with data structures. The evaluation results of SEED as a pedagogical mediator in the issue of binary trees is presented. The evaluation indicates that students prefer to use SEED due to its simplicity and attractive GUIs which facilitate data structures learning.

Forensic analysis is to determine the causes of compromise security of a system. At present general rules and principles as the International Organization for Digital Evidence (IOCE) they are known. The aim of the study was to characterize Colombian law as to the specific and necessary for the design of computer technical regulations regarding the extraction of digital evidence to anchor the chain of custody. A descriptive documentary research and applied type was used, by analyzing different sources on information systems, integrity, confidentiality and availability of data in judicial custody. Current regulations allow substantiate the use of computer techniques to extract digital evidence and ensure the chain of custody, based on the constitutional protection of the right to privacy, so they must respect freedom and promote other warranties. Regulations also relies on Law 527 of August 18, 1999 which is magnetic and software tools, as well as the law 527 of 1999 on electronic commerce for Colombia, Law 1273 of 2009 for the protection of information and Law 1273 of 2009 which criminalizes cybercrime. Palabras clave:Análisis forense, delito informático, sistema de información, normatividad. ResumenEl análisis forense consiste en determinar las causas del compromiso de seguridad de un sistema. En la actualidad se conocen normas y principios generales como la Organización Internacional en Evidencia Digital (IOCE). El objetivo del estudio fue caracterizar la legislación colombiana en cuanto a la normatividad específica y necesaria para el diseño de la técnica informática en cuanto a la extracción de la evidencia digital para anclar la cadena de custodia. Se utilizó una investigación descriptiva de tipo documental y aplicada, mediante el análisis de diferentes fuentes sobre sistemas de información, integridad, confidencialidad y disponibilidad de datos bajo custodia judicial. La normatividad actual permite fundamentar el uso de técnicas informáticas para la extracción de la evidencia digital y asegurar la cadena de custodia, basado en la protección constitucional del derecho a la intimidad, por lo que se deben respetar la libertad y promover las demás garantías. También la normatividad se apoya en la Ley 527 de Agosto 18 de 1999 que trata de los instrumentos magnéticos e informáticos, así como la ley 527 de 1999 sobre el comercio electrónico para Colombia, la Ley 1273 de 2009 para la protección de la información y la Ley 1273 del 2009 que tipifica los delitos informáticos.

Web service composition requires high levels of integration and reliability of the services involved in its operation, which must meet specific quality criteria to ensure their proper execution and deployment. The discovery and selection of web services currently face optimization problems. Many services might satisfy a requirement with similar quality criteria. Because of this, software developers have to choose the most appropriate services for a given composition, complicated by the rapid increase in providers and services available in the cloud. Service composition also implies coupling according to a composition flow and non-functional requirement criteria. Such requirements make selection and composition a complex task not previously solved in the literature. This paper presents Ar_WSDS, a computational approach for web services discovery and selection in cloud environments, which bases its implementation on the brain’s pattern recognition systematic functioning. This process allows classifying web services through recognition modules created dynamically based on their quality parameters, resulting in a set of web services suitable for a web service composition. This approach allows a solution to the selection problem using less complex tasks. This paper introduces an architectural and procedural definition that provides the web service description with a pattern to recognize and select services using different recognition levels. We simulated our approach and evaluated it using a dataset from the QWS project that offers a set of quality criteria collected from different providers. The web services are recognized and classified using different quality criteria for the composition and each of their services. The results demonstrate the effectiveness of the discovery and selection process compared to other approaches. Furthermore, Ar_WSDS allows us to recognize and filter out web services with ambiguity and similarity in their provider information, a process that minimizes the discovery space for services.

There are optimization problems in the Cloud for the selection of web services, due to the large number of services available by different cloud providers and the diversity of quality of service parameters of each of them. This work proposes the adaptation of a pattern recognition model based on the systematic functioning of the brain called Ar2p for the selection of web services in composition activities in Cloud environments. The web serice are represented as patterns to be recognized by Ar2p, which determines the necessary and sufficient web services that constitute the composition of services that meet its functional and non-functional requirements. The services composition and activity selection have been formalized through a logical-mathematical model of web service recognition mechanisms in two steps, one that describes the syntactic search of the service and the second, which offers filtering through quality of service parameters. An adaptive implementation of the final model allows its recognition modules to be provided with any desired optimization strategy.

Concerning computational physics, web services are conceived as mathematical units that are experienced in different systems that offer service composition. Due to the exponential growth of web services and their deployment on cloud platforms, quality of service parameters have now become an essential factor when searching for and selecting services that must satisfy specific non-functional requirements of a user application. A variety of service components are highly configurable and are dynamic scenarios because a significant number of services can meet these requirements. This work analyzes the systemic perspective of approaches for the selecting and searching of web services that have specifications of optimization strategies based on the configurable quality of service parameters with test scenarios in cloud environments that have a considerable number of services as input. The study shows that policies based on artificial intelligence and related areas are the ones with the most significant convergence, and the approaches analyzed to give a perspective of future work aimed at strategies based on automatic learning.