923 resultados para AUTOMATED SOFTWARE ENGINEERING
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This book provides the latest in a series of books growing out of the International Joint Conferences on Computer, Information and Systems Sciences and Engineering. It includes chapters in the most advanced areas of Computing, Informatics, Systems Sciences and Engineering. It has accessible to a wide range of readership, including professors, researchers, practitioners and students. This book includes a set of rigorously reviewed world-class manuscripts addressing and detailing state-of-the-art research projects in the areas of Computer Science, Informatics, and Systems Sciences, and Engineering. It includes selected papers form the conference proceedings of the Ninth International Joint Conferences on Computer, Information, and Systems Sciences, and Engineering (CISSE 2013). Coverage includes topics in: Industrial Electronics, Technology & Automation, Telecommunications and Networking, Systems, Computing Sciences and Software Engineering, Engineering Education, Instructional Technology, Assessment, and E-learning.
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ABSTRACT ONTOLOGIES AND METHODS FOR INTEROPERABILITY OF ENGINEERING ANALYSIS MODELS (EAMS) IN AN E-DESIGN ENVIRONMENT SEPTEMBER 2007 NEELIMA KANURI, B.S., BIRLA INSTITUTE OF TECHNOLOGY AND SCIENCES PILANI INDIA M.S., UNIVERSITY OF MASSACHUSETTS AMHERST Directed by: Professor Ian Grosse Interoperability is the ability of two or more systems to exchange and reuse information efficiently. This thesis presents new techniques for interoperating engineering tools using ontologies as the basis for representing, visualizing, reasoning about, and securely exchanging abstract engineering knowledge between software systems. The specific engineering domain that is the primary focus of this report is the modeling knowledge associated with the development of engineering analysis models (EAMs). This abstract modeling knowledge has been used to support integration of analysis and optimization tools in iSIGHT FD , a commercial engineering environment. ANSYS , a commercial FEA tool, has been wrapped as an analysis service available inside of iSIGHT-FD. Engineering analysis modeling (EAM) ontology has been developed and instantiated to form a knowledge base for representing analysis modeling knowledge. The instances of the knowledge base are the analysis models of real world applications. To illustrate how abstract modeling knowledge can be exploited for useful purposes, a cantilever I-Beam design optimization problem has been used as a test bed proof-of-concept application. Two distinct finite element models of the I-beam are available to analyze a given beam design- a beam-element finite element model with potentially lower accuracy but significantly reduced computational costs and a high fidelity, high cost, shell-element finite element model. The goal is to obtain an optimized I-beam design at minimum computational expense. An intelligent KB tool was developed and implemented in FiPER . This tool reasons about the modeling knowledge to intelligently shift between the beam and the shell element models during an optimization process to select the best analysis model for a given optimization design state. In addition to improved interoperability and design optimization, methods are developed and presented that demonstrate the ability to operate on ontological knowledge bases to perform important engineering tasks. One such method is the automatic technical report generation method which converts the modeling knowledge associated with an analysis model to a flat technical report. The second method is a secure knowledge sharing method which allocates permissions to portions of knowledge to control knowledge access and sharing. Both the methods acting together enable recipient specific fine grain controlled knowledge viewing and sharing in an engineering workflow integration environment, such as iSIGHT-FD. These methods together play a very efficient role in reducing the large scale inefficiencies existing in current product design and development cycles due to poor knowledge sharing and reuse between people and software engineering tools. This work is a significant advance in both understanding and application of integration of knowledge in a distributed engineering design framework.
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Course materials for e-learning are a special type of information system (IS). Thus, in the development of educational material one may learn from principles, methods, and tools that originated in the Software Engineering (SE) discipline and that are relevant in similar ways in "Instructional Engineering". An important SE principle is mo dularization, which supports properties like reusability and adaptability of code. To foster the adaptability of courseware we present a concept in which learning material is organized as a library of modular course objects. A certain lecturer may customize the courseware according to his specific course requirements. He must consider logical dependencies of and relationship integrity between selected course objects. We discuss integrity issues that have to be regarded for the composition of consistent course materials.
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Usability is the capability of the software product to be understood, learned, used and attractive to the user, when used under specified conditions. Many studies demonstrate the benefits of usability, yet to this day software products continue to exhibit consistently low levels of this quality attribute. Furthermore, poor usability in software systems contributes largely to software failing in actual use. One of the main disciplines involved in usability is that of Human-Computer Interaction (HCI). Over the past two decades the HCI community has proposed specific features that should be present in applications to improve their usability, yet incorporating them into software continues to be far from trivial for software developers. These difficulties are due to multiple factors, including the high level of abstraction at which these HCI recommendations are made and how far removed they are from actual software implementation. In order to bridge this gap, the Software Engineering community has long proposed software design solutions to help developers include usability features into software, however, the problem remains an open research question. This doctoral thesis addresses the problem of helping software developers include specific usability features into their applications by providing them with a structured and tangible guidance in the form of a process, which we have termed the Usability-Oriented Software Development Process. This process is supported by a set of Software Usability Guidelines that help developers to incorporate a set of eleven usability features with high impact on software design. After developing the Usability-oriented Software Development Process and the Software Usability Guidelines, they have been validated across multiple academic projects and proven to help software developers to include such usability features into their software applications. In doing so, their use significantly reduced development time and improved the quality of the resulting designs of these projects. Furthermore, in this work we propose a software tool to automate the application of the proposed process. In sum, this work contributes to the integration of the Software Engineering and HCI disciplines providing a framework that helps software developers to create usable applications in an efficient way.
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For years, the Human Computer Interaction (HCI) community has crafted usability guidelines that clearly define what characteristics a software system should have in order to be easy to use. However, in the Software Engineering (SE) community keep falling short of successfully incorporating these recommendations into software projects. From a SE perspective, the process of incorporating usability features into software is not always straightforward, as a large number of these features have heavy implications in the underlying software architecture. For example, successfully including an “undo” feature in an application requires the design and implementation of many complex interrelated data structures and functionalities. Our work is focused upon providing developers with a set of software design patterns to assist them in the process of designing more usable software. This would contribute to the proper inclusion of specific usability features with high impact on the software design. Preliminary validation data show that usage of the guidelines also has positive effects on development time and overall software design quality.
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The runtime management of the infrastructure providing service-based systems is a complex task, up to the point where manual operation struggles to be cost effective. As the functionality is provided by a set of dynamically composed distributed services, in order to achieve a management objective multiple operations have to be applied over the distributed elements of the managed infrastructure. Moreover, the manager must cope with the highly heterogeneous characteristics and management interfaces of the runtime resources. With this in mind, this paper proposes to support the configuration and deployment of services with an automated closed control loop. The automation is enabled by the definition of a generic information model, which captures all the information relevant to the management of the services with the same abstractions, describing the runtime elements, service dependencies, and business objectives. On top of that, a technique based on satisfiability is described which automatically diagnoses the state of the managed environment and obtains the required changes for correcting it (e.g., installation, service binding, update, or configuration). The results from a set of case studies extracted from the banking domain are provided to validate the feasibility of this proposa
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Replication of software engineering experiments is crucial for dealing with validity threats to experiments in this area. Even though the empirical software engineering community is aware of the importance of replication, the replication rate is still very low. The RESER'11 Joint Replication Project aims to tackle this problem by simultaneously running a series of several replications of the same experiment. In this article, we report the results of the replication run at the Universidad Politécnica de Madrid. Our results are inconsistent with the original experiment. However, we have identified possible causes for them. We also discuss our experiences (in terms of pros and cons) during the replication.
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In computer science, different types of reusable components for building software applications were proposed as a direct consequence of the emergence of new software programming paradigms. The success of these components for building applications depends on factors such as the flexibility in their combination or the facility for their selection in centralised or distributed environments such as internet. In this article, we propose a general type of reusable component, called primitive of representation, inspired by a knowledge-based approach that can promote reusability. The proposal can be understood as a generalisation of existing partial solutions that is applicable to both software and knowledge engineering for the development of hybrid applications that integrate conventional and knowledge based techniques. The article presents the structure and use of the component and describes our recent experience in the development of real-world applications based on this approach.
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Software testing is a key aspect of software reliability and quality assurance in a context where software development constantly has to overcome mammoth challenges in a continuously changing environment. One of the characteristics of software testing is that it has a large intellectual capital component and can thus benefit from the use of the experience gained from past projects. Software testing can, then, potentially benefit from solutions provided by the knowledge management discipline. There are in fact a number of proposals concerning effective knowledge management related to several software engineering processes. Objective: We defend the use of a lesson learned system for software testing. The reason is that such a system is an effective knowledge management resource enabling testers and managers to take advantage of the experience locked away in the brains of the testers. To do this, the experience has to be gathered, disseminated and reused. Method: After analyzing the proposals for managing software testing experience, significant weaknesses have been detected in the current systems of this type. The architectural model proposed here for lesson learned systems is designed to try to avoid these weaknesses. This model (i) defines the structure of the software testing lessons learned; (ii) sets up procedures for lesson learned management; and (iii) supports the design of software tools to manage the lessons learned. Results: A different approach, based on the management of the lessons learned that software testing engineers gather from everyday experience, with two basic goals: usefulness and applicability. Conclusion: The architectural model proposed here lays the groundwork to overcome the obstacles to sharing and reusing experience gained in the software testing and test management. As such, it provides guidance for developing software testing lesson learned systems.
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Software Configuration Management (SCM) techniques have been considered the entry point to rigorous software engineering, where multiple organizations cooperate in a decentralized mode to save resources, ensure the quality of the diversity of software products, and manage corporate information to get a better return of investment. The incessant trend of Global Software Development (GSD) and the complexity of implementing a correct SCM solution grow not only because of the changing circumstances, but also because of the interactions and the forces related to GSD activities. This paper addresses the role SCM plays in the development of commercial products and systems, and introduces a SCM reference model to describe the relationships between the different technical, organizational, and product concerns any software development company should support in the global market.
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The focus of this paper is to outline the main structure of an alternative software process improvement method for small- and medium-size enterprises. This method is based on the action package concept, which helps to institutionalize the effective practices with affordable implementation costs. This paper also presents the results and lessons learned when this method was applied to three enterprises in the requirements engineering domain.
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Abstract?Background: There is no globally accepted open source software development process to define how open source software is developed in practice. A process description is important for coordinating all the software development activities involving both people and technology. Aim: The research question that this study sets out to answer is: What activities do open source software process models contain? The activity groups on which it focuses are Concept Exploration, Software Requirements, Design, Maintenance and Evaluation. Method: We conduct a systematic mapping study (SMS). A SMS is a form of systematic literature review that aims to identify and classify available research papers concerning a particular issue. Results: We located a total of 29 primary studies, which we categorized by the open source software project that they examine and by activity types (Concept Exploration, Software Requirements, Design, Maintenance and Evaluation). The activities present in most of the open source software development processes were Execute Tests and Conduct Reviews, which belong to the Evaluation activities group. Maintenance is the only group that has primary studies addressing all the activities that it contains. Conclusions: The primary studies located by the SMS are the starting point for analyzing the open source software development process and proposing a process model for this community. The papers in our paper pool that describe a specific open source software project provide more regarding our research question than the papers that talk about open source software development without referring to a specific open source software project.
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An accepted fact in software engineering is that software must undergo verification and validation process during development to ascertain and improve its quality level. But there are too many techniques than a single developer could master, yet, it is impossible to be certain that software is free of defects. So, it is crucial for developers to be able to choose from available evaluation techniques, the one most suitable and likely to yield optimum quality results for different products. Though, some knowledge is available on the strengths and weaknesses of the available software quality assurance techniques but not much is known yet on the relationship between different techniques and contextual behavior of the techniques. Objective: This research investigates the effectiveness of two testing techniques ? equivalence class partitioning and decision coverage and one review technique ? code review by abstraction, in terms of their fault detection capability. This will be used to strengthen the practical knowledge available on these techniques.
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La Ingeniería del Software Empírico (ISE) utiliza como herramientas los estudios empíricos para conseguir evidencias que ayuden a conocer bajo qué circunstancias es mejor usar una tecnología software en lugar de otra. La investigación en la que se enmarca este TFM explora si las intuiciones y/o preferencias de las personas que realizan las pruebas de software, son capaces de predecir la efectividad de tres técnicas de evaluación de código: lectura por abstracciones sucesivas, cobertura de decisión y partición en clases de equivalencia. Para conseguir dicho objetivo, se analizan los datos recogidos en un estudio empírico, realizado por las tutoras de este TFM. En el estudio empírico distintos sujetos aplican las tres técnicas de evaluación de código a tres programas distintos, a los que se les habían introducido una serie de faltas artificialmente. Los sujetos deben reportar los fallos encontrados en los programas, así como, contestar a una serie de preguntas sobre sus intuiciones y preferencias. A la hora de analizar los datos del estudio, se ha comprobado: 1) cuáles son sus intuiciones y preferencias (mediante el test estadístico X2 de Pearson); 2) si los sujetos cambian de opinión después de aplicar las técnicas (para ello se ha utilizado índice de Kappa, el Test de McNemar-Bowker y el Test de Stuart-Maxwell); 3) la consistencia de las distintas preguntas (mediante el índice de Kappa), comparando: intuiciones con intuiciones, preferencias con preferencias e intuiciones con preferencias; 4) Por último, si hay coincidencia entre las intuiciones y preferencias con la efectividad real obtenida (para ello se ha utilizado, el Modelo Lineal General con medidas repetidas). Los resultados muestran que, no hay una intuición clara ni tampoco una preferencia concreta, con respecto a los programas. Además aunque existen cambios de opinión después de aplicar las técnicas, no se encuentran evidencias claras para afirmar que la intuición y preferencias influyen en su efectividad. Finalmente, existen relaciones entre las intuiciones con intuiciones, preferencias con preferencias e intuiciones con preferencias, además esta relación es más notoria después de aplicar las técnicas. ----ABSTRACT----Empirical Software Engineering (ESE) uses empirical studies as a mean to generate evidences to help determine under what circumstances it is convenient to use a given software technology. This Master Thesis is part of a research that explores whether intuitions and/or preferences of testers, can be used to predict the effectiveness of three code evaluation techniques: reading by stepwise abstractions, decision coverage and equivalence partitioning. To achieve this goal, this Master Thesis analyzes the data collected in an empirical study run by the tutors. In the empirical study, different subjects apply three code evaluation techniques to three different programs. A series of faults were artificially introduced to the programs. Subjects are required to report the defects found in the programs, as well as answer a series of questions about their intuitions and preferences. The data analyses test: 1) what are the intuitions and preferences of the subjects (using the Pearson X2 test); 2) whether subjects change their minds after applying the techniques (using the Kappa coefficient, McNemar-Bowker test, and Stuart-Maxwell test); 3) the consistency of the different questions, comparing: intuitions versus intuitions, preferences versus preferences and preferences versus intuitions (using the Kappa coefficient); 4) finally, if intuitions and/or preferences predict the actual effectiveness obtained (using the General Linear Model, repeated measures). The results show that there is not clear intuition or particular preference with respect to the programs. Moreover, although there are changes of mind after applying the techniques, there are not clear evidences to claim that intuition and preferences influence their effectiveness. Finally, there is a relationship between the intuitions versus intuitions, preferences versus preferences and intuitions versus preferences; this relationship is more noticeable after applying the techniques.