918 resultados para Model Based Testing
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The work described in this Master’s Degree thesis was born after the collaboration with the company Maserati S.p.a, an Italian luxury car maker with its headquarters located in Modena, in the heart of the Italian Motor Valley, where I worked as a stagiaire in the Virtual Engineering team between September 2021 and February 2022. This work proposes the validation using real-world ECUs of a Driver Drowsiness Detection (DDD) system prototype based on different detection methods with the goal to overcome input signal losses and system failures. Detection methods of different categories have been chosen from literature and merged with the goal of utilizing the benefits of each of them, overcoming their limitations and limiting as much as possible their degree of intrusiveness to prevent any kind of driving distraction: an image processing-based technique for human physical signals detection as well as methods based on driver-vehicle interaction are used. A Driver-In-the-Loop simulator is used to gather real data on which a Machine Learning-based algorithm will be trained and validated. These data come from the tests that the company conducts in its daily activities so confidential information about the simulator and the drivers will be omitted. Although the impact of the proposed system is not remarkable and there is still work to do in all its elements, the results indicate the main advantages of the system in terms of robustness against subsystem failures and signal losses.
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The issues influencing student engagement with high-stakes computer-based exams were investigated, drawing on feedback from two cohorts of international MA Education students encountering this assessment method for the first time. Qualitative data from surveys and focus groups on the students’ examination experience were analysed, leading to the identification of engagement issues in the delivery of high-stakes computer-based assessments.The exam combined short-answer open-response questions with multiple-choice-style items to assess knowledge and understanding of research methods. The findings suggest that engagement with computer-based testing depends, to a lesser extent, on students’ general levels of digital literacy and, to a greater extent, on their information technology (IT) proficiency for assessment and their ability to adapt their test-taking strategies, including organisational and cognitive strategies, to the online assessment environment. The socialisation and preparation of students for computer-based testing therefore emerge as key responsibilities for instructors to address, with students requesting increased opportunities for practice and training to develop the IT skills and test-taking strategies necessary to succeed in computer-based examinations. These findings and their implications in terms of instructional responsibilities form the basis of a proposal for a framework for Learner Engagement with e-Assessment Practices.
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Abstract — The analytical methods based on evaluation models of interactive systems were proposed as an alternative to user testing in the last stages of the software development due to its costs. However, the use of isolated behavioral models of the system limits the results of the analytical methods. An example of these limitations relates to the fact that they are unable to identify implementation issues that will impact on usability. With the introduction of model-based testing we are enable to test if the implemented software meets the specified model. This paper presents an model-based approach for test cases generation from the static analysis of source code.
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Testaustapausten valitseminen on testauksessa tärkeää, koska kaikkia testaustapauksia ei voida testata aika- ja raharajoitteiden takia. Testaustapausten valintaan on paljon eri menetelmiä joista eniten esillä olevat ovat malleihin perustuva valinta, kombinaatiovalinta ja riskeihin perustuva valinta. Kaikkiin edellä mainittuihin menetelmiin testaustapaukset luodaan ohjelman spesifikaation perusteella. Malleihin perustuvassa menetelmässä käytetään hyväksi ohjelman toiminnasta olevia malleja, joista valitaan tärkeimmät testattavaksi. Kombinaatiotestauksessa testitapaukset on muodostettu ominaisuuspareina jolloin yhden parin testaamisesta päätellään kahden ominaisuuden toiminta. Kombinaatiotestaus on tehokas löytämään virheitä, jotka johtuvat yhdestä tai kahdesta tekijästä. Riskeihin perustuva testaus pyrkii arvioimaan ohjelman riskejä ja valitsemaan testitapaukset niiden perusteella. Kaikissa menetelmissä priorisointi on tärkeässä roolissa, jotta testauksesta saadaan riittävä luotettavuus ilman kustannusten nousua.
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With the increasing complexity of software systems, there is also an increased concern about its faults. These faults can cause financial losses and even loss of life. Therefore, we propose in this paper the minimization of faults in software by using formally specified tests. The combination of testing and formal specifications is gaining strength in searches mainly through the MBT (Model-Based Testing). The development of software from formal specifications, when the whole process of refinement is done rigorously, ensures that what is specified in the application will be implemented. Thus, the implementation generated from these specifications would accurately depict what was specified. But not always the specification is refined to the level of implementation and code generation, and in these cases the tests generated from the specification tend to find fault. Additionally, the generation of so-called "invalid tests", ie tests that exercise the application scenarios that were not addressed in the specification, complements more significantly the formal development process. Therefore, this paper proposes a method for generating tests from B formal specifications. This method was structured in pseudo-code. The method is based on the systematization of the techniques of black box testing of boundary value analysis, equivalence partitioning, as well as the technique of orthogonal pairs. The method was applied to a B specification and B test machines that generate test cases independent of implementation language were generated. Aiming to validate the method, test cases were transformed manually in JUnit test cases and the application, created from the B specification and developed in Java, was tested. Faults were found with the execution of the JUnit test cases
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Formal methods and software testing are tools to obtain and control software quality. When used together, they provide mechanisms for software specification, verification and error detection. Even though formal methods allow software to be mathematically verified, they are not enough to assure that a system is free of faults, thus, software testing techniques are necessary to complement the process of verification and validation of a system. Model Based Testing techniques allow tests to be generated from other software artifacts such as specifications and abstract models. Using formal specifications as basis for test creation, we can generate better quality tests, because these specifications are usually precise and free of ambiguity. Fernanda Souza (2009) proposed a method to define test cases from B Method specifications. This method used information from the machine s invariant and the operation s precondition to define positive and negative test cases for an operation, using equivalent class partitioning and boundary value analysis based techniques. However, the method proposed in 2009 was not automated and had conceptual deficiencies like, for instance, it did not fit in a well defined coverage criteria classification. We started our work with a case study that applied the method in an example of B specification from the industry. Based in this case study we ve obtained subsidies to improve it. In our work we evolved the proposed method, rewriting it and adding characteristics to make it compatible with a test classification used by the community. We also improved the method to support specifications structured in different components, to use information from the operation s behavior on the test case generation process and to use new coverage criterias. Besides, we have implemented a tool to automate the method and we have submitted it to more complex case studies
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Esta tesis trata de las llamadas relaciones de conformidad que pueden darse entre dos sistemas cualesquiera, especificación e implementación. Como novedad introduce el uso de técnicas coinductivas para la definición de iocos, una relación de conformidad capaz de distinguir el contexto local de ejecución de un proceso. Al constituir iocos la parte central de una nueva teoría de Model Based Testing (MBT), se precisa de una descripción formal de los sistemas en juego; esto se lleva a cabo en primera instancia mediante sistemas de transiciones etiquetadas y posteriormente mediante un enfoque más abstracto, un álgebra de procesos. Las teorías de testing tienen por objeto confirmar las relaciones de conformidad mediante la ejecución de un conjunto de tests sobre un sistema –la implementación– cuya estructura interna se desconoce. Particularmente los beneficios de un enfoque MBT son inmediatos, ya que la generación de los tests puede abordarse de manera sistemática una vez se disponga de un modelo formal de la especificación, lo que contribuye a eliminar el error imputable al factor humano; esto se logra dando un algoritmo generador de tests que toma cono entrada una especificación y produce un conjunto de tests, posiblemente infinito, suficientemente representativo para asegurar la relación de conformidad. Este enfoque inicial, conocido como testing offline o testing estático, es mejorado para ganar en eficiencia evitando un alto consumo en recursos tanto de tiempo como de memoria mediante la técnica de testing online o testing dinámico, donde ambos pasos de generación y ejecución se ejecutan de manera alternada...
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O Teste Baseado em Modelos (TBM) emergiu como uma estratégia promissora para minimizar problemas relacionados à falta de tempo e recursos em teste de software e visa verificar se a implementação sob teste está em conformidade com sua especificação. Casos de teste são gerados automaticamente a partir de modelos comportamentais produzidos durante o ciclo de desenvolvimento de software. Entre as técnicas de modelagem existentes, Sistemas de Transição com Entrada/Saída (do inglês, Input/Output Transition Systems - IOTSs), são modelos amplamente utilizados no TBM por serem mais expressivos do que Máquinas de Estado Finito (MEFs). Apesar dos métodos existentes para geração de testes a partir de IOTSs, o problema da seleção de casos de testes é um tópico difícil e importante. Os métodos existentes para IOTS são não-determinísticos, ao contrário da teoria existente para MEFs, que fornece garantia de cobertura completa com base em um modelo de defeitos. Esta tese investiga a aplicação de modelos de defeitos em métodos determinísticos de geração de testes a partir de IOTSs. Foi proposto um método para geração de conjuntos de teste com base no método W para MEFs. O método gera conjuntos de teste de forma determinística além de satisfazer condições de suficiência de cobertura da especificação e de todos os defeitos do domínio de defeitos definido. Estudos empíricos avaliaram a aplicabilidade e eficácia do método proposto: resultados experimentais para analisar o custo de geração de conjuntos de teste utilizando IOTSs gerados aleatoriamente e um estudo de caso com especificações da indústria mostram a efetividade dos conjuntos gerados em relação ao método tradicional de Tretmans.
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Modern software application testing, such as the testing of software driven by graphical user interfaces (GUIs) or leveraging event-driven architectures in general, requires paying careful attention to context. Model-based testing (MBT) approaches first acquire a model of an application, then use the model to construct test cases covering relevant contexts. A major shortcoming of state-of-the-art automated model-based testing is that many test cases proposed by the model are not actually executable. These \textit{infeasible} test cases threaten the integrity of the entire model-based suite, and any coverage of contexts the suite aims to provide. In this research, I develop and evaluate a novel approach for classifying the feasibility of test cases. I identify a set of pertinent features for the classifier, and develop novel methods for extracting these features from the outputs of MBT tools. I use a supervised logistic regression approach to obtain a model of test case feasibility from a randomly selected training suite of test cases. I evaluate this approach with a set of experiments. The outcomes of this investigation are as follows: I confirm that infeasibility is prevalent in MBT, even for test suites designed to cover a relatively small number of unique contexts. I confirm that the frequency of infeasibility varies widely across applications. I develop and train a binary classifier for feasibility with average overall error, false positive, and false negative rates under 5\%. I find that unique event IDs are key features of the feasibility classifier, while model-specific event types are not. I construct three types of features from the event IDs associated with test cases, and evaluate the relative effectiveness of each within the classifier. To support this study, I also develop a number of tools and infrastructure components for scalable execution of automated jobs, which use state-of-the-art container and continuous integration technologies to enable parallel test execution and the persistence of all experimental artifacts.
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Dissertação (mestrado)—Universidade de Brasília, Instituto de Ciências Exatas, Departamento de Ciência da Computação, 2015.
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This work deals with the development of calibration procedures and control systems to improve the performance and efficiency of modern spark ignition turbocharged engines. The algorithms developed are used to optimize and manage the spark advance and the air-to-fuel ratio to control the knock and the exhaust gas temperature at the turbine inlet. The described work falls within the activity that the research group started in the previous years with the industrial partner Ferrari S.p.a. . The first chapter deals with the development of a control-oriented engine simulator based on a neural network approach, with which the main combustion indexes can be simulated. The second chapter deals with the development of a procedure to calibrate offline the spark advance and the air-to-fuel ratio to run the engine under knock-limited conditions and with the maximum admissible exhaust gas temperature at the turbine inlet. This procedure is then converted into a model-based control system and validated with a Software in the Loop approach using the engine simulator developed in the first chapter. Finally, it is implemented in a rapid control prototyping hardware to manage the combustion in steady-state and transient operating conditions at the test bench. The third chapter deals with the study of an innovative and cheap sensor for the in-cylinder pressure measurement, which is a piezoelectric washer that can be installed between the spark plug and the engine head. The signal generated by this kind of sensor is studied, developing a specific algorithm to adjust the value of the knock index in real-time. Finally, with the engine simulator developed in the first chapter, it is demonstrated that the innovative sensor can be coupled with the control system described in the second chapter and that the performance obtained could be the same reachable with the standard in-cylinder pressure sensors.
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This paper describes the design, implementation and testing of an intelligent knowledge-based supervisory control (IKBSC) system for a hot rolling mill process. A novel architecture is used to integrate an expert system with an existing supervisory control system and a new optimization methodology for scheduling the soaking pits in which the material is heated prior to rolling. The resulting IKBSC system was applied to an aluminium hot rolling mill process to improve the shape quality of low-gauge plate and to optimise the use of the soaking pits to reduce energy consumption. The results from the trials demonstrate the advantages to be gained from the IKBSC system that integrates knowledge contained within data, plant and human resources with existing model-based systems. (c) 2005 Elsevier Ltd. All rights reserved.
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Report published in the Proceedings of the National Conference on "Education and Research in the Information Society", Plovdiv, May, 2015
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Statistical association between a single nucleotide polymorphism (SNP) genotype and a quantitative trait in genome-wide association studies is usually assessed using a linear regression model, or, in the case of non-normally distributed trait values, using the Kruskal-Wallis test. While linear regression models assume an additive mode of inheritance via equi-distant genotype scores, Kruskal-Wallis test merely tests global differences in trait values associated with the three genotype groups. Both approaches thus exhibit suboptimal power when the underlying inheritance mode is dominant or recessive. Furthermore, these tests do not perform well in the common situations when only a few trait values are available in a rare genotype category (disbalance), or when the values associated with the three genotype categories exhibit unequal variance (variance heterogeneity). We propose a maximum test based on Marcus-type multiple contrast test for relative effect sizes. This test allows model-specific testing of either dominant, additive or recessive mode of inheritance, and it is robust against variance heterogeneity. We show how to obtain mode-specific simultaneous confidence intervals for the relative effect sizes to aid in interpreting the biological relevance of the results. Further, we discuss the use of a related all-pairwise comparisons contrast test with range preserving confidence intervals as an alternative to Kruskal-Wallis heterogeneity test. We applied the proposed maximum test to the Bogalusa Heart Study dataset, and gained a remarkable increase in the power to detect association, particularly for rare genotypes. Our simulation study also demonstrated that the proposed non-parametric tests control family-wise error rate in the presence of non-normality and variance heterogeneity contrary to the standard parametric approaches. We provide a publicly available R library nparcomp that can be used to estimate simultaneous confidence intervals or compatible multiplicity-adjusted p-values associated with the proposed maximum test.
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OBJECTIVES: The complexity and heterogeneity of human bone, as well as ethical issues, most always hinder the performance of clinical trials. Thus, in vitro studies become an important source of information for the understanding of biomechanical events on implant-supported prostheses, although study results cannot be considered reliable unless validation studies are conducted. The purpose of this work was to validate an artificial experimental model based on its modulus of elasticity, to simulate the performance of human bone in vivo in biomechanical studies of implant-supported prostheses. MATERIAL AND METHODS: In this study, fast-curing polyurethane (F16 polyurethane, Axson) was used to build 40 specimens that were divided into five groups. The following reagent ratios (part A/part B) were used: Group A (0.5/1.0), Group B (0.8/1.0), Group C (1.0/1.0), Group D (1.2/1.0), and Group E (1.5/1.0). A universal testing machine (Kratos model K - 2000 MP) was used to measure modulus of elasticity values by compression. RESULTS: Mean modulus of elasticity values were: Group A - 389.72 MPa, Group B - 529.19 MPa, Group C - 571.11 MPa, Group D - 470.35 MPa, Group E - 437.36 MPa. CONCLUSION: The best mechanical characteristics and modulus of elasticity value comparable to that of human trabecular bone were obtained when A/B ratio was 1:1.