998 resultados para coverage test


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In testing from a Finite State Machine (FSM), the generation of test suites which guarantee full fault detection, known as complete test suites, has been a long-standing research topic. In this paper, we present conditions that are sufficient for a test suite to be complete. We demonstrate that the existing conditions are special cases of the proposed ones. An algorithm that checks whether a given test suite is complete is given. The experimental results show that the algorithm can be used for relatively large FSMs and test suites.

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To plan testing activities, testers face the challenge of determining a strategy, including a test coverage criterion that offers an acceptable compromise between the available resources and test goals. Known theoretical properties of coverage criteria do not always help and, thus, empirical data are needed. The results of an experimental evaluation of several coverage criteria for finite state machines (FSMs) are presented, namely, state and transition coverage; initialisation fault and transition fault coverage. The first two criteria focus on FSM structure, whereas the other two on potential faults in FSM implementations. The authors elaborate a comparison approach that includes random generation of FSM, construction of an adequate test suite and test minimisation for each criterion to ensure that tests are obtained in a uniform way. The last step uses an improved greedy algorithm.

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In this paper, we consider a classical problem of complete test generation for deterministic finite-state machines (FSMs) in a more general setting. The first generalization is that the number of states in implementation FSMs can even be smaller than that of the specification FSM. Previous work deals only with the case when the implementation FSMs are allowed to have the same number of states as the specification FSM. This generalization provides more options to the test designer: when traditional methods trigger a test explosion for large specification machines, tests with a lower, but yet guaranteed, fault coverage can still be generated. The second generalization is that tests can be generated starting with a user-defined test suite, by incrementally extending it until the desired fault coverage is achieved. Solving the generalized test derivation problem, we formulate sufficient conditions for test suite completeness weaker than the existing ones and use them to elaborate an algorithm that can be used both for extending user-defined test suites to achieve the desired fault coverage and for test generation. We present the experimental results that indicate that the proposed algorithm allows obtaining a trade-off between the length and fault coverage of test suites.

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Modern Integrated Circuit (IC) design is characterized by a strong trend of Intellectual Property (IP) core integration into complex system-on-chip (SOC) architectures. These cores require thorough verification of their functionality to avoid erroneous behavior in the final device. Formal verification methods are capable of detecting any design bug. However, due to state explosion, their use remains limited to small circuits. Alternatively, simulation-based verification can explore hardware descriptions of any size, although the corresponding stimulus generation, as well as functional coverage definition, must be carefully planned to guarantee its efficacy. In general, static input space optimization methodologies have shown better efficiency and results than, for instance, Coverage Directed Verification (CDV) techniques, although they act on different facets of the monitored system and are not exclusive. This work presents a constrained-random simulation-based functional verification methodology where, on the basis of the Parameter Domains (PD) formalism, irrelevant and invalid test case scenarios are removed from the input space. To this purpose, a tool to automatically generate PD-based stimuli sources was developed. Additionally, we have developed a second tool to generate functional coverage models that fit exactly to the PD-based input space. Both the input stimuli and coverage model enhancements, resulted in a notable testbench efficiency increase, if compared to testbenches with traditional stimulation and coverage scenarios: 22% simulation time reduction when generating stimuli with our PD-based stimuli sources (still with a conventional coverage model), and 56% simulation time reduction when combining our stimuli sources with their corresponding, automatically generated, coverage models.

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OBJECTIVE: To identify clustering areas of infants exposed to HIV during pregnancy and their association with indicators of primary care coverage and socioeconomic condition. METHODS: Ecological study where the unit of analysis was primary care coverage areas in the city of Porto Alegre, Southern Brazil, in 2003. Geographical Information System and spatial analysis tools were used to describe indicators of primary care coverage areas and socioeconomic condition, and estimate the prevalence of liveborn infants exposed to HIV during pregnancy and delivery. Data was obtained from Brazilian national databases. The association between different indicators was assessed using Spearman's nonparametric test. RESULTS: There was found an association between HIV infection and high birth rates (r=0.22, p<0.01) and lack of prenatal care (r=0.15, p<0.05). The highest HIV infection rates were seen in areas with poor socioeconomic conditions and difficult access to health services (r=0.28, p<0.01). The association found between higher rate of prenatal care among HIV-infected women and adequate immunization coverage (r=0.35, p<0.01) indicates that early detection of HIV infection is effective in those areas with better primary care services. CONCLUSIONS: Urban poverty is a strong determinant of mother-to-child HIV transmission but this trend can be fought with health surveillance at the primary care level.

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OBJECTIVE To analyze the coverage of a cervical cancer screening program in a city with a high incidence of the disease in addition to the factors associated with non-adherence to the current preventive program.METHODS A cross-sectional study based on household surveys was conducted. The sample was composed of women between 25 and 59 years of age of the city of Boa Vista, RR, Northern Brazil who were covered by the cervical cancer screening program. The cluster sampling method was used. The dependent variable was participation in a women’s health program, defined as undergoing at least one Pap smear in the 36 months prior to the interview; the explanatory variables were extracted from individual data. A generalized linear model was used.RESULTS 603 women were analyzed, with an mean age of 38.2 years (SD = 10.2). Five hundred and seventeen women underwent the screening test, and the prevalence of adherence in the last three years was up to 85.7% (95%CI 82.5;88.5). A high per capita household income and recent medical consultation were associated with the lower rate of not being tested in multivariate analysis. Disease ignorance, causes, and prevention methods were correlated with chances of non-adherence to the screening system; 20.0% of the women were reported to have undergone opportunistic and non-routine screening.CONCLUSIONS The informed level of coverage is high, exceeding the level recommended for the control of cervical cancer. The preventive program appears to be opportunistic in nature, particularly for the most vulnerable women (with low income and little information on the disease). Studies on the diagnostic quality of cervicovaginal cytology and therapeutic schedules for positive cases are necessary for understanding the barriers to the control of cervical cancer.

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From March 1991 to April 1992, serum samples for IgM detection were collected from 112 clinical measles cases reported to the Health Department of Niterói, State of Rio de Janeiro. The positivity exceeded 90% for specimens collected from the 5th to the 29th day after the onset of the disease. After day 30 a decline in IgM detection was observed, although positivity has been detected up to 90 days after the onset of the symptoms. Forty-four patients (48.9%) with an IgM response had a history of prior measles vaccination. In 5 of the 22 measles-IgM negative cases the infection was due to other agents (rubella: 4 cases, dengue: 1 case). These results show that sensitivity of the test employed for confirming suspected measles cases is high, even in vaccinated patients.

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IP networks are currently the major communication infrastructure used by an increasing number of applications and heterogeneous services, including voice services. In this context, the Session Initiation Protocol (SIP) is a signaling protocol widely used for controlling multimedia communication sessions such as voice or video calls over IP networks, thus performing vital functions in an extensive set of public and enter- prise solutions. However, the SIP protocol dissemination also entails some challenges, such as the complexity associated with the testing/validation processes of IMS/SIP networks. As a consequence, manual IMS/SIP testing solutions are inherently costly and time consuming tasks, being crucial to develop automated approaches in this specific area. In this perspective, this article presents an experimental approach for automated testing/validation of SIP scenarios in IMS networks. For that purpose, an automation framework is proposed allowing to replicate the configuration of SIP equipment from the pro- duction network and submit such equipment to a battery of tests in the testing network. The proposed solution allows to drastically reduce the test and validation times when compared with traditional manual approaches, also allowing to enhance testing reliability and coverage. The automation framework comprises of some freely available tools which are conveniently integrated with other specific modules implemented within the context of this work. In order to illustrate the advantages of the proposed automated framework, a real case study taken from a PT Inovação customer is presented comparing the time required to perform a manual SIP testing approach with the one time required when using the proposed auto- mated framework. The presented results clearly corroborate the advantages of using the presented framework.

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BACKGROUND: HIV-1 RNA viral load is a key parameter for reliable treatment monitoring of HIV-1 infection. Accurate HIV-1 RNA quantitation can be impaired by primer and probe sequence polymorphisms as a result of tremendous genetic diversity and ongoing evolution of HIV-1. A novel dual HIV-1 target amplification approach was realized in the quantitative COBAS AmpliPrep/COBAS TaqMan HIV-1 Test, v2.0 (HIV-1 TaqMan test v2.0) to cope with the high genetic diversity of the virus. OBJECTIVES AND STUDY DESIGN: The performance of the new assay was evaluated for sensitivity, dynamic range, precision, subtype inclusivity, diagnostic and analytical specificity, interfering substances, and correlation with the COBAS AmpliPrep/COBAS TaqMan HIV-1 (HIV-1 TaqMan test v1.0) predecessor test in patients specimens. RESULTS: The new assay demonstrated a sensitivity of 20 copies/mL, a linear measuring range of 20-10,000,000 copies/mL, with a lower limit of quantitation of 20 copies/mL. HIV-1 Group M subtypes and HIV-1 Group O were quantified within +/-0.3 log(10) of the assigned titers. Specificity was 100% in 660 tested specimens, no cross reactivity was found for 15 pathogens nor any interference for endogenous substances or 29 drugs. Good comparability with the predecessor assay was demonstrated in 82 positive patient samples. In selected clinical samples 35/66 specimens were found underquantitated in the predecessor assay; all were quantitated correctly in the new assay. CONCLUSIONS: The dual-target approach for the HIV-1 TaqMan test v2.0 enables superior HIV-1 Group M subtype coverage including HIV-1 Group O detection. Correct quantitation of specimens underquantitated in the HIV-1 TaqMan test v1.0 test was demonstrated.

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Premature failure of concrete pavement contraction joint seals is an ongoing and costly problem for the Iowa Department of Transportation. Several joint seal test sections consisting of variations in sawing methods, joint cleaning techniques, sealant installation, and sealant types have been established over the past few years. Laboratory analysis and field inspections were done as a part of the tests, and core samples were taken for laboratory adhesion pull tests. Such methods often cover specifically small areas and may not expose hidden failures. Some tests are also labor-intensive and destructive, especially that of coring. An innovative, nondestructive, broad coverage joint seal tester that yields quick results has been designed and developed for evaluation of pavement joint seal performance. The Iowa vacuum joint seal tester (IA-VAC) applies a low vacuum above a joint seal that has been spray-covered with a foaming water solution. Any unsealed area or leak that exists along the joint will become quickly and clearly visible by the development of bubbles at the leak point. By analyzing the results from the IA-VAC tests, information on the number and types of leaks can be obtained; such information will help identify the source of the problem and direct efforts toward a solution.

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Quantifying the spatial configuration of hydraulic conductivity (K) in heterogeneous geological environments is essential for accurate predictions of contaminant transport, but is difficult because of the inherent limitations in resolution and coverage associated with traditional hydrological measurements. To address this issue, we consider crosshole and surface-based electrical resistivity geophysical measurements, collected in time during a saline tracer experiment. We use a Bayesian Markov-chain-Monte-Carlo (McMC) methodology to jointly invert the dynamic resistivity data, together with borehole tracer concentration data, to generate multiple posterior realizations of K that are consistent with all available information. We do this within a coupled inversion framework, whereby the geophysical and hydrological forward models are linked through an uncertain relationship between electrical resistivity and concentration. To minimize computational expense, a facies-based subsurface parameterization is developed. The Bayesian-McMC methodology allows us to explore the potential benefits of including the geophysical data into the inverse problem by examining their effect on our ability to identify fast flowpaths in the subsurface, and their impact on hydrological prediction uncertainty. Using a complex, geostatistically generated, two-dimensional numerical example representative of a fluvial environment, we demonstrate that flow model calibration is improved and prediction error is decreased when the electrical resistivity data are included. The worth of the geophysical data is found to be greatest for long spatial correlation lengths of subsurface heterogeneity with respect to wellbore separation, where flow and transport are largely controlled by highly connected flowpaths.

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Modern sophisticated telecommunication devices require even more and more comprehensive testing to ensure quality. The test case amount to ensure well enough coverage of testing has increased rapidly and this increased demand cannot be fulfilled anymore only by using manual testing. Also new agile development models require execution of all test cases with every iteration. This has lead manufactures to use test automation more than ever to achieve adequate testing coverage and quality. This thesis is separated into three parts. Evolution of cellular networks is presented at the beginning of the first part. Also software testing, test automation and the influence of development model for testing are examined in the first part. The second part describes a process which was used to implement test automation scheme for functional testing of LTE core network MME element. In implementation of the test automation scheme agile development models and Robot Framework test automation tool were used. In the third part two alternative models are presented for integrating this test automation scheme as part of a continuous integration process. As a result, the test automation scheme for functional testing was implemented. Almost all new functional level testing test cases can now be automated with this scheme. In addition, two models for integrating this scheme to be part of a wider continuous integration pipe were introduced. Also shift from usage of a traditional waterfall model to a new agile development based model in testing stated to be successful.

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In order to evaluate the performance of a 1-h 75-g oral glucose tolerance test (OGTT) for the diagnosis of gestational diabetes mellitus (GDM), a cohort of 4998 women, 20 years or older, without previous diabetes being treated in prenatal care clinics in Brazil answered a questionnaire and performed a 75-g OGTT including fasting, 1-h and 2-h glucose measurements between their 24th and 28th gestational weeks. Pregnancy outcomes were transcribed from medical registries. GDM was defined according to WHO criteria (fasting: ≥126 mg/dL; 2-h value: ≥140 mg/dL) and macrosomia as a birth weight equal to or higher than 4000 g. Areas under the receiver operator characteristic curve (AUC) were compared and diagnostic properties of various cut-off points were evaluated. The AUCs for the prediction of macrosomia were 0.606 (0.572-0.637) for the 1-h and 0.589 (0.557-0.622) for the 2-h plasma glucose test. Similar predictability was demonstrable regarding combined adverse outcomes: 0.582 (0.559-0.604) for the 1-h test and 0.572 (0.549-0.595) for the 2-h test. When the 1-h glucose test was evaluated against a diagnosis of GDM defined by the 2-h glucose test, the AUC was 0.903 (0.886-0.919). The cut-off point that maximized sensitivity (83%) and specificity (83%) was 141 mg/dL, identifying 21% of the women as positive. A cut-off point of 160 mg/dL, with lower sensitivity (62%), had higher specificity (94%), labeling 8.6% as positive. Detection of GDM can be done with a 1-h 75-g OGTT: the value of 160 mg/dL has the same diagnostic performance as the conventional 2-h value (140 mg/dL). The simplification of the test may improve coverage and timing of the diagnosis of GDM.