The frailty approach is commonly used in reliability theory and survival analysis to model the dependence between lifetimes of individuals or components subject to common risk factors; according to this model the frailty (an unobservable random vector that describes environmental conditions) acts simultaneously on the hazard functions of the lifetimes. Some interesting conditions for stochastic comparisons between random vectors defined in accordance with these models have been described in the literature; in particular, comparisons between frailty models have been studied by assuming independence for the baseline survival functions and the corresponding environmental parameters. In this paper, a generalization of these models is developed, which assumes conditional dependence between the components of the random vector, and some conditions for stochastic comparisons are provided. Some examples of frailty models satisfying these conditions are also described.
Testing in Software Engineering is one of the most important phases although, unfortunately, it cannot be always successfully fulfilled due to time constraints. In most cases, the development phase takes more time than it was estimated, entailing negative effects on the testing phase. The delay increases even more in Research and Development (R + D) projects, where the real time to execute tasks is more difficult to control. Model Driven Engineering (MDE) offers a solution to avoid testing costs without affecting the execution quality of the applied test. This paper presents a practical overview of a Model Driven Testing (MDT)-based methodology and its impact on CA-LIPSOneo project, which was carried out in liaison with Airbus Defense and Space and, particularly, with the Product Lifecycle Management (PLM) department.
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