Recent Studies in Software Reliability Engineering

Pham, Hoang

doi:10.1007/1-85233-841-5_16

Cited by 17 publications

(11 citation statements)

References 32 publications

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“…The high availability of monitoring data allows, nowadays, to compute valuable and accurate characterization of both the actual software behavior and the usage profile. The original approaches tended to consider the software system as a black-box and to observe its reliability from the outside [22]. Most recent trends are focused on modular or component-based systems [23] and assume an architectural-level perspective [4].…”

Section: Related Workmentioning

confidence: 99%

Reliability analysis in Symbolic PathFinder

Filieri

Păsăreanu

Visser

2013

2013 35th International Conference on Software Engineering (ICSE)

155

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Abstract-Software reliability analysis tackles the problem of predicting the failure probability of software. Most of the current approaches base reliability analysis on architectural abstractions useful at early stages of design, but not directly applicable to source code. In this paper we propose a general methodology that exploit symbolic execution of source code for extracting failure and success paths to be used for probabilistic reliability assessment against relevant usage scenarios. Under the assumption of finite and countable input domains, we provide an efficient implementation based on Symbolic PathFinder that supports the analysis of sequential and parallel programs, even with structured data types, at the desired level of confidence. The tool has been validated on both NASA prototypes and other test cases showing a promising applicability scope.

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Section: Related Workmentioning

confidence: 99%

Reliability analysis in Symbolic PathFinder

Filieri

Păsăreanu

Visser

2013

2013 35th International Conference on Software Engineering (ICSE)

155

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“…Three types of dependence among track sections can be considered, namely stochastic dependence, structural dependence and economic dependence. The existence of stochastic dependence (Pham, 2003;Thomas, 1986;Castanier, Grall, & B erenguer, 2005) means that the degradation in one track section may influence the degradation of other track sections. This dependence was proved by Andrade & Teixeira (2011) and .…”

Section: Introductionmentioning

confidence: 99%

Optimal opportunistic tamping scheduling for railway track geometry

Khajehei

Haddadzade

Ahmadi

et al. 2020

Structure and Infrastructure Engineering

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This study has been dedicated to the optimization of opportunistic tamping scheduling. The aim of this study has been to schedule tamping activities in such a way that the total maintenance costs and the number of unplanned tamping activities are minimized. To achieve this, the track geometry tamping scheduling problem was defined and formulated as a mixed integer linear programming (MILP) model and a genetic algorithm was used to solve the problem. Both the standard deviation of the longitudinal level and the extreme values of isolated defects were used to characterize the track geometry quality and to plan maintenance activities. The performance of the proposed model was tested on data collected from the Main Western Line in Sweden. The results show that different scenarios for controlling and managing isolated defects will result in optimal scheduling plan. It is also found that to achieve more realistic results, the speed of the tamping machine and the unused life of the track sections should be considered in the model. Moreover, the results show that prediction of geometry condition without considering the destructive effect of tamping will lead to an underestimation of the maintenance needs by 2%.

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“…Some efforts have been made in transportation research [24] and traffic policy [25]. Recently, copulas have been successfully applied in reliability analysis in civil [26], mechanical and structural [27], offshore [28] and software [29] engineering. In Biology, copulas have been used in the field of genetics [30] to model gene dependencies.…”

Section: Introductionmentioning

confidence: 99%

Analysis of the Parametric Correlation in Mathematical Modeling of In Vitro Glioblastoma Evolution Using Copulas

et al. 2020

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Modeling and simulation are essential tools for better understanding complex biological processes, such as cancer evolution. However, the resulting mathematical models are often highly non-linear and include many parameters, which, in many cases, are difficult to estimate and present strong correlations. Therefore, a proper parametric analysis is mandatory. Following a previous work in which we modeled the in vitro evolution of Glioblastoma Multiforme (GBM) under hypoxic conditions, we analyze and solve here the problem found of parametric correlation. With this aim, we develop a methodology based on copulas to approximate the multidimensional probability density function of the correlated parameters. Once the model is defined, we analyze the experimental setting to optimize the utility of each configuration in terms of gathered information. We prove that experimental configurations with oxygen gradient and high cell concentration have the highest utility when we want to separate correlated effects in our experimental design. We demonstrate that copulas are an adequate tool to analyze highly-correlated multiparametric mathematical models such as those appearing in Biology, with the added value of providing key information for the optimal design of experiments, reducing time and cost in in vivo and in vitro experimental campaigns, like those required in microfluidic models of GBM evolution.

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Recent Studies in Software Reliability Engineering

Cited by 17 publications

References 32 publications

Reliability analysis in Symbolic PathFinder

Reliability analysis in Symbolic PathFinder

Optimal opportunistic tamping scheduling for railway track geometry

Analysis of the Parametric Correlation in Mathematical Modeling of In Vitro Glioblastoma Evolution Using Copulas

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