To model damage accumulation for load-sharing systems, two models given by intensity functions of self-exciting point processes are proposed: a model with additive damage accumulation and a model with multiplicative damage accumulation. Both models include the model without damage accumulation as a special case. For both models, the likelihood functions are derived and maximum likelihood estimators and likelihood ratio tests are given in a scale-invariant version and a scale-dependent version. Furthermore, a Bayesian approach using Markov chain Monte Carlo methods for posterior computation is provided. The frequentist and Bayesian methods are applied to a data set of failures of tension wires of concrete beams where a significant damage accumulation effect is confirmed by both additive and multiplicative damage accumulation models. This is all the more remarkable as a simulation study indicates that the tests for an existing damage accumulation effect are rather conservative. Moreover, prediction intervals for the failure times of the tension wires in a new experiment are given, which improve former prediction intervals derived without damage accumulation. The simulation study considers a scenario with a fixed time horizon and one with fixed numbers of failed components of the systems.

OOPS is an object-oriented programming environment with integrated data management facilities. It is designed to especially support advanced applications, like engineering and office applications. Rich data modeling facilities, including the concepts of classification, generalization, and aggregation are provided. Additionally, complex semantic integrity constraints, exception-handling mechanisms, and triggers can be specified. Since all these facilities are integrated into a single language, the artificial distinction between database language and programming language is no longer existent. The main features of the programming language and the architecture of OOPS are presented.>