Evaluation of Blood Assays for Detection of Mycobacterium bovis in White-Tailed Deer (Odocoileus virginianus) in Michigan

Surveillance and control activities related to bovine tuberculosis (TB) in free-ranging, Michigan white-tailed deer (Odocoileus virginianus) have been underway for over a decade, with significant progress. However, foci of higher TB prevalence on private lands and limited agency ability to eliminate them using broad control strategies have led to development and trial of new control strategies, such as live trapping, testing, and culling or release. Such strategies require a prompt, accurate live animal test, which has thus far been lacking. We report here the ability of seven candidate blood assays to determine the TB infection status of Michigan deer. Our aims were twofold: to characterize the accuracy of the tests using field-collected samples and to evaluate the feasibility of the tests for use in a test-and-cull strategy. Samples were collected from 760 deer obtained via five different surveys conducted between 2004 and 2007. Blood samples were subjected to one or more of the candidate blood assays and evaluated against the results of mycobacterial culture of the cranial lymph nodes. Sensitivities of the tests ranged from 46% to 68%, whereas specificities and negative predictive values were all .92%. Positive predictive values were highly variable. An exploratory analysis of associations among several host and sampling-related factors and the agreement between blood assay and culture results suggested these assays were minimally affected. This study demonstrated the capabilities and limitations of several available blood tests for Mycobacterium bovis on specimens obtained through a variety of field surveillance methods. Although these blood assays cannot replace mass culling, information on their performance may prove useful as wildlife disease managers develop innovative methods of detecting infected animals where mass culling is publicly unacceptable and cannot be used as a control strategy.

Designing Software Product Lines for Testability

Software product line (SPL) engineering offers several advantages in the development of families of software products such as reduced costs, high quality and a short time to market. A software product line is a set of software intensive systems, each of which shares a common core set of functionalities, but also differs from the other products through customization tailored to fit the needs of individual groups of customers. The differences between products within the family are well-understood and organized into a feature model that represents the variability of the SPL. Products can then be built by generating and composing features described in the feature model. Testing of software product lines has become a bottleneck in the SPL development lifecycle, since many of the techniques used in their testing have been borrowed from traditional software testing and do not directly take advantage of the similarities between products. This limits the overall gains that can be achieved in SPL engineering. Recent work proposed by both industry and the research community for improving SPL testing has begun to consider this problem, but there is still a need for better testing techniques that are tailored to SPL development. In this thesis, I make two primary contributions to software product line testing. First I propose a new definition for testability of SPLs that is based on the ability to re-use test cases between products without a loss of fault detection effectiveness. I build on this idea to identify elements of the feature model that contribute positively and/or negatively towards SPL testability. Second, I provide a graph based testing approach called the FIG Basis Path method that selects products and features for testing based on a feature dependency graph. This method should increase our ability to re-use results of test cases across successive products in the family and reduce testing effort. I report the results of a case study involving several non-trivial SPLs and show that for these objects, the FIG Basis Path method is as effective as testing all products, but requires us to test no more than 24% of the products in the SPL.