Applications and Potentials for Biogenic Methane Recovery Operations in Nebraska Agriculture, Industry, and Economic Development

ABSTRACT: This thesis report illustrates the applications and potentials of biogenic methane recovery in Nebraska’s agricultural and industrial sectors and as a means for increasing sustainable economic development in the state’s rural communities. As the nation moves toward a new green economy, biogenic methane recovery as a waste management strategy and renewable energy resource presents significant opportunities for Nebraska to be a national and world leader in agricultural and industrial innovation, advanced research and development of renewable energy technology, and generation of new product markets. Nebraska’s agricultural economy provides a distinct advantage to the state for supporting methane recovery operations that provide long-term economic and environmental partnerships among producers, industry, and communities. These opportunities will serve to protect Nebraska’s agricultural producers from volatile energy input markets and as well as creating new markets for Nebraska agricultural products. They will also serve to provide quality education and employment opportunities for Nebraska students and businesses. There are challenges and issues that remain for the state in order to take advantage of its resource potential. There is a need to produce a comprehensive Nebraska biogenic methane potential study and digital mapping system to identify high-potential producers, co-products, and markets. There is also a need to develop a web-based format of consolidated information specific to Nebraska to aid in connecting producers, service providers, educators, and policy-makers.

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.