the outcomes of the subsequent operational test. In the workshop session on combining information, Duane Steffey described use of a parametric hierarchical Bayes framework for combining data from related experiments, and Francisco Samaniego followed with a description of nonparametric methods for handling the same problem. These presenters argued that existing methods and others under current investigation constitute promising ways of modeling the data-combination challenges that arise in developmental and operational testing.
Some of the earliest work on fatigue modeling occurred in the context of addressing problems that were common in the aircraft industry during and following World War II. While some of the early attempts at modeling fatigue in the materials used in aircraft construction were primarily mathematical in nature, the field has evolved and seen some notable advances and achievements through the collaboration of mathematical/statistical workers, materials engineers, and other scientists. Sam Saunders described some of the early work in this area at Boeing, including the development of the widely used Birnbaum-Saunders model, and underscored the importance of understanding the science involved in a particular application before attempting to model the problem statistically. Joe Padgett’s presentation was focused on a class of models for fatigue of materials or systems due to cumulative damage and the modeling of crack growth due to fatigue. This work, which combines current thinking in materials science and sophisticated statistical modeling, provides a broad collection of models on which to base estimation and prediction in this area.
Modern military systems have become increasingly dependent on computer software for their successful and reliable operation. Given that the area of software reliability is broad enough to merit a workshop of its own, the goal of the session was scaled down to providing the flavor of two particular lines of research in the area. Siddhartha Dalal’s presentation focused on efficient methods of selecting factorial experiments with attractive coverage possibilities. He described approaches to experimental design that allow the experimenter to sample a reasonably broad array of combinations of factors while controlling the scale of the overall experiment. Jesse Poore’s presentation focused on methods of testing software that take special account of anticipated usage patterns, thereby enhancing the likelihood of good performance in the software’s intended domains of application.