18 research outputs found

    Robotlu kaynak üretim hattı tasarımı

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    Otomotiv sektöründe, robotlar özellikle gövde, kaporta atölyeleri, boyahane ve pres hane bölümlerinde yaygın olarak kullanılmaktadır Ülkemizde bu sektörünün hızla ilerlemesiyle ve rekabet koşullarının araç üreticilerini yeni model üretimine zorlaması, canlı bir hat entegrasyon sektörüne sebep olmuştur. Robotlar, eğer üretim ve ürün robotlu uygulamaya uygun olarak tasarlanmışsa yüksek performansla çalışır. Hat entegrasyonu yapan firma, tasarım aşamasından başlayarak, ürün modülerliği ve standartlaşması sağlandığında, hızlı ve kolay robotlu üretime geçiş sağlanır

    Robotlu üretim hattı entegrasyonu

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    Otomotiv sektöründe, robotlar özellikle gövde, kaporta atölyeleri, boyahane ve preshane bölümlerinde yaygın olarak kullanılmaktadır Ülkemizde bu sektörünün hızla ilerlemesiyle ve rekabet koşullarının araç üreticilerini yeni model üretimine zorlaması, canlı bir hat entegrasyon sektörüne sebep olmuştur. Robotlar, eğer üretim ve ürün robotlu uygulamaya uygun olarak tasarlanmışsa yüksek performansla çalışır. Hat entegrasyonu yapan firma, tasarım aşamasından başlayarak, ürün modülerliği ve standartlaşması sağlandığında, hızlı ve kolay robotlu üretime geçiş sağlanır. Yazılım sistemin esnekliğinin temel elemanlarındandır. Yazılım güvenliği, belirli süre belirli ortamda hatasız olarak çalışması ile ölçülür. Yazılım sağlamlığı, sistemin güvenilirliğinin temeldir. Donanımsal güvenlikten farklı olarak tasarım mükemmelliğinin göstergesidir

    Predicting Requirements Change Propagation Based on Software Architecture

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    Change propagation is a central issue in software development process. In early stages of software development, software architecture facilitates the component-based software development process and provides a platform for prediction of requirements change. Keywords: software architecture, requirements change propagation, architectural pattern This paper aims to predict change propagation in early stages of software development, and evaluate the architecture based on architectural pattern. In order to achieve this goal, the change propagation probability is formally defined, and the change propagation in five architectural patterns is discussed. Moreover, change propagation density is defined to extend the pattern-based propagation, which incorporates design metrics into software architecture evaluation. The efficiency of the proposed method is demonstrated through a computational experiment

    An evaluation of the software architecture efficiency using the Clichés and behavioral diagrams pertaining to the unified modeling language

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    The software architecture plays essential role for the development of the complicated software systems and it is important to evaluate the software architecture efficiency. One way to evaluate the software architecture is to create an executable model from the architecture. Unified Modeling Language (UML) diagrams are used to describe the software architecture. UML has made it easy to use and to evaluate the necessary requirements at the software architecture level. It creates an executable model from these diagrams; yet, since the UML is a standard semi-formal language for describing the software architecture, evaluating the software architecture is not directly possible through it. Furthermore, in order to evaluate the software architecture, one needs to turn the actual model into the formal model. In this study, first we describe the architecture using the UML. Then, some properties of the software architecture are mentioned using the UML sequence diagram, deployment diagram, use case diagram, and component diagram. The necessary information associated with the qualitative characteristic of efficiency will be margined as clichés and labels to these diagrams. The independent and dependent components will be extracted from the component diagram. Finally, the resulted semi-formal model will be mapped into a formal model based on the colored Petri net and finally the evaluation will take place

    A Large-Scale Industrial Case Study on Architecture-Based Software Reliability Analysis

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    Abstract—Architecture-based software reliability analysis methods shall help software architects to identify critical software components and to quantify their influence on the system reliability. Although researchers have proposed more than 20 methods in this area, empirical case studies applying these methods on large-scale industrial systems are rare. The costs and benefits of these methods remain unknown. On this behalf, we have applied the Cheung method on the software architecture of an industrial control system from ABB consisting of more than 100 components organized in nine subsystems with more than three million lines of code. We used the Littlewood/Verrall model to estimate subsystems failure rates and logging data to derive subsystem transition probabilities. We constructed a discrete time Markov chain as an architectural model and conducted a sensitivity analysis. This paper summarizes our experiences and lessons learned. We found that architecture-based software reliability analysis is still difficult to apply and that more effective data collection techniques are required. Keywords-Software reliability growth, software architecture, Markov processes I

    Formal approach on modeling and predicting of software system security: Stochastic petri net

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    To evaluate and predict component-based software security, a two-dimensional model of software security is proposed by Stochastic Petri Net in this paper. In this approach, the software security is modeled by graphical presentation ability of Petri nets, and the quantitative prediction is provided by the evaluation capability of Stochastic Petri Net and the computing power of Markov chain. Each vulnerable component is modeled by Stochastic Petri net and two parameters, Successfully Attack Probability (SAP) and Vulnerability Volume of each component to another component. The second parameter, as a second dimension of security evaluation, is a metric that is added to modeling to improve the accuracy of the result of system security prediction. An isomorphic Markov chain is obtained from a corresponding SPN model. The security prediction is calculated based on the probability distribution of the MC in the steady state. To identify and trace back to the critical points of system security, a sensitive analysis method is applied by derivation of the security prediction equation. It provides the possibility to investigate and compare different solutions with the target system in the designing phase

    Strategy for scalable scenarios modeling and calculation in early software reliability engineering

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    System scenarios derived from requirements specification play an important role in the early software reliability engineering. A great deal of research effort has been devoted to predict reliability of a system at early design stages. The existing approaches are unable to handle scalability and calculation of scenarios reliability for large systems. This paper proposes modeling of scenarios in a scalable way by using a scenario language that describes system scenarios in a compact and concise manner which can results in a reduced number of scenarios. Furthermore, it proposes a calculation strategy to achieve better traceability of scenarios, and avoid computational complexity. The scenarios are pragmatically modeled and translated to finite state machines, where each state machine represents the behaviour of component instance within the scenario. The probability of failure of each component exhibited in the scenario is calculated separately based on the finite state machines. Finally, the reliability of the whole scenario is calculated based on the components’ behaviour models and their failure information using modified mathematical formula. In this paper, an example related to a case study of an automated railcar system is used to verify and validate the proposed strategy for scalability of system modeling

    A Dynamical Reliability Prediction Algorithm for Composite Service

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    Dynamic selection and dynamic binding and rebinding at runtime are new characters of composite services. The traditional static reliability prediction models are unsuitable to dynamic composite services. A new reliability predicting algorithm for composite services is proposed in this paper. Firstly, a composite service is decomposed into composition unites (executing path, composite module and atomic service) according to their constituents. Consequently, a hierarchical graph of all composite units is constructed. Lastly, a new dynamic reliability prediction algorithm is presented. Comparing with the traditional reliability model, the new dynamic reliability approach is more flexible, which does not recompute reliability for all composite units and only computes the reliability of the effected composite units. In addition, an example to show how to measure the reliability based on our algorithm is designed. The experimental results show our proposed methods can give an accurate estimation of reliability. Furthermore, a more flexible sensitivity analysis is performed to determine which service component has the most significant impact on the improvement of composite service reliability

    Un Enfoque Inteligente para Soporte a la Toma de Decisiones de Diseño Arquitectónicas en el Contexto de la Evaluación de Arquitecturas de Software

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    La Ingeniería de Software necesita herramientas novedosas para alcanzar alta calidad en el software, enfrentando el rol cambiante del mismo. La Arquitectura de Software es clave, ya que afecta directamente a la calidad final. La Evaluación de Arquitecturas de Software valida si la arquitectura cumple con los requerimientos de calidad, implicando decisiones de diseño. La toma de decisiones es un proceso complejo conducido por factores humanos, donde la Inteligencia Artificial puede asistir. Entonces, se propone un enfoque basado en Inteligencia Artificial para ayudar a arquitectos en el proceso de toma de decisiones de diseño conducido por atributos de calidad. Esta versión combina modelos de atributos de calidad y un Agente inteligente, utilizando Aprendizaje por Refuerzo para obtener una política de aplicación de patrones arquitectónicos secuencial mediante simulación. Un estudio de caso y una serie de experimentos ilustran la propuesta con patrones comúnmente utilizados en la industria del software.Fil: Bogado, Verónica Soledad. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Centro de Investigaciones y Transferencia de Villa María. Universidad Nacional de Villa María. Centro de Investigaciones y Transferencia de Villa María; ArgentinaFil: Villarreal Guzmán, Eva. Departamento Ingeniería En Sistemas de Información; ArgentinaFil: Gonnet, Silvio Miguel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; ArgentinaFil: Leone, Horacio Pascual. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; Argentin

    Reliability in open source software

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    Open Source Software is a component or an application whose source code is freely accessible and changeable by the users, subject to constraints expressed in a number of licensing modes. It implies a global alliance for developing quality software with quick bug fixing along with quick evolution of the software features. In the recent year tendency toward adoption of OSS in industrial projects has swiftly increased. Many commercial products use OSS in various fields such as embedded systems, web management systems, and mobile software’s. In addition to these, many OSSs are modified and adopted in software products. According to Netcarf survey more than 58% web servers are using an open source web server, Apache. The swift increase in the taking on of the open source technology is due to its availability, and affordability. Recent empirical research published by Forrester highlighted that although many European software companies have a clear OSS adoption strategy; there are fears and questions about the adoption. All these fears and concerns can be traced back to the quality and reliability of OSS. Reliability is one of the more important characteristics of software quality when considered for commercial use. It is defined as the probability of failure free operation of software for a specified period of time in a specified environment (IEEE Std. 1633-2008). While open source projects routinely provide information about community activity, number of developers and the number of users or downloads, this is not enough to convey information about reliability. Software reliability growth models (SRGM) are frequently used in the literature for the characterization of reliability in industrial software. These models assume that reliability grows after a defect has been detected and fixed. SRGM is a prominent class of software reliability models (SRM). SRM is a mathematical expression that specifies the general form of the software failure process as a function of factors such as fault introduction, fault removal, and the operational environment. Due to defect identification and removal the failure rate (failures per unit of time) of a software system generally decreases over time. Software reliability modeling is done to estimate the form of the curve of the failure rate by statistically estimating the parameters associated with the selected model. The purpose of this measure is twofold: 1) to estimate the extra test time required to meet a specified reliability objective and 2) to identify the expected reliability of the software after release (IEEE Std. 1633-2008). SRGM can be applied to guide the test board in their decision of whether to stop or continue the testing. These models are grouped into concave and S-Shaped models on the basis of assumption about cumulative failure occurrence pattern. The S-Shaped models assume that the occurrence pattern of cumulative number of failures is S-Shaped: initially the testers are not familiar with the product, then they become more familiar and hence there is a slow increase in fault removing. As the testers’ skills improve the rate of uncovering defects increases quickly and then levels off as the residual errors become more difficult to remove. In the concave shaped models the increase in failure intensity reaches a peak before a decrease in failure pattern is observed. Therefore the concave models indicate that the failure intensity is expected to decrease exponentially after a peak was reached. From exhaustive study of the literature I come across three research gaps: SRGM have widely been used for reliability characterization of closed source software (CSS), but 1) there is no universally applicable model that can be applied in all cases, 2) applicability of SRGM for OSS is unclear and 3) there is no agreement on how to select the best model among several alternative models, and no specific empirical methodologies have been proposed, especially for OSS. My PhD work mainly focuses on these three research gaps. In first step, focusing on the first research gap, I analyzed comparatively eight SRGM, including Musa Okumoto, Inflection S-Shaped, Geol Okumoto, Delayed S-Shaped, Logistic, Gompertz and Generalized Geol, in term of their fitting and prediction capabilities. These models have selected due to their wide spread use and they are the most representative in their category. For this study 38 failure datasets of 38 projects have been used. Among 38 projects, 6 were OSS and 32 were CSS. In 32 CSS datasets 22 were from testing phase and remaining 10 were from operational phase (i.e. field). The outcomes show that Musa Okumoto remains the best for CSS projects while Inflection S-Shaped and Gompertz remain best for OSS projects. Apart from that we observe that concave models outperform for CSS and S-Shaped outperform for OSS projects. In the second step, focusing on the second research gap, reliability growth of OSS projects was compared with that of CSS projects. For this purpose 25 OSS and 22 CSS projects were selected with related defect data. Eight SRGM were fitted to the defect data of selected projects and the reliability growth was analyzed with respect to fitted models. I found that the entire selected models fitted to OSS projects defect data in the same manner as that of CSS projects and hence it confirms that OSS projects reliability grows similarly to that of CSS projects. However, I observed that for OSS S-Shaped models outperform and for CSS concave shaped models outperform. To overcome the third research gap I proposed a method that selects the best SRGM among several alternative models for predicting the residuals of an OSS. The method helps the practitioners in deciding whether to adopt an OSS component, or not in a project. We test the method empirically by applying it to twenty one different releases of seven OSS projects. From the validation results it is clear that the method selects the best model 17 times out of 21. In the remaining four it selects the second best model
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