Fail-Safe Testing of Web Applications

This dissertation introduces an approach to generate tests to test fail-safe behavior for web applications. We apply the approach to a commercial web application. We build models for both behavioral and mitigation requirements. We create mitigation tests from an existing functional black box test suite by determining failure type and points of failure in the test suite and weaving required mitigation based on weaving rules to generate a test suite that tests proper mitigation of failures. A genetic algorithm (GA) is used to determine points of failure and type of failure that needs to be tested. Mitigation test paths are woven into the behavioral test at the point of failure based on failure specific weaving rules. A simulator was developed to evaluate choice of parameters for the genetic algorithm. We showed how to tune the fitness function and performed tuning experiments for GA to determine what values to use for exploration weight and prospecting weight. We found that higher defect densities make prospecting and mining more successful, while lower mitigation defect densities need more exploration. We compare efficiency and effectiveness of the approach. First, the GA approach is compared to random selection. The results show that the GA performance was better than random selection and that the approach was robust when the search space increased. Second, we compare the GA against four coverage criteria. The results of comparison show that test requirements generated by a genetic algorithm (GA) are more efficient than three of the four coverage criteria for large search spaces. They are equally effective. For small search spaces, the genetic algorithm is less effective than three of the four coverage criteria. The fourth coverage criteria is too weak and unable to find all defects in almost all cases. We also present a large case study of a mortgage system at one of our industrial partners and show how we formalize the approach. We evaluate the use of a GA to create test requirements. The evaluation includes choice of initial population, multiplicity of runs and a discussion of the cost of evaluating fitness. Finally, we build a selective regression testing approach based on types of changes (add, delete, or modify) that could occur in the behavioral model, the fault model, the mitigation models, the weaving rules, and the state-event matrix. We provide a systematic method by showing the formalization steps for each type of change to the various models.

Genetically Engineered Crops: A Study of Major Environmental Implications and U.S. Policy

The adoption of genetically modified crops is becoming evermore common in United States agriculture. However, this relatively new technology carries a negative stigma and perceived risks that have resulted commonly in public disapproval. In the United States, bioengineered crops are highly regulated. The significance of environmental benefits such as decreased chemical impact, increased soil conservation, heightened carbon sequestration, decreased energy demands, and reduced air emissions, are important enough to warrant a revision to U.S. policy. The U.S. policy structure needs to be simplified and made more efficient to better facilitate the speed with which new GE products can, and should, be developed while still providing adequate mitigation of potential environmental risks such as species invasiveness and impacts on non-target species.

Improving the Success of Wetland Mitigation Banking: Lessons Learned in Monitoring and Compliance

Wetlands that are lost to development are not effectively compensated by the current wetland mitigation banking regulatory program due to inadequate monitoring and compliance. Based on a critical investigation of two wetland mitigation banks in Colorado described herein, recommendations are given to improve the effectiveness of the wetland mitigation banking program. The recommendations to improve mitigation banking are to specify and follow comprehensive monitoring and reporting plans, develop solid contingency and adaptive management plans, utilize specially developed checklists and templates, and impose enforcement when compliance is not met. Implementing these recommendations will assist regulators and bankers in achieving more effective wetland mitigation and will help the United States reach its no net loss of wetlands goal.

Potential Adverse Effects of the Alaska Natural Gas Pipeline on Arctic Caribou and Proposed Mitigation

The Alaska Natural Gas Pipeline (ANGP) is proposed for construction on the North Slope in 2016. It will be aligned through Arctic caribou habitat and evidence shows that caribou are negatively affected by human development. This Capstone identifies potential adverse affects of ANGP on Arctic caribou using interviews from expert caribou biologists and the 1977 Trans-Alaska Pipeline System (TAPS) as a model. Based on a synthesis of the interviews and TAPS analysis, this capstone proposes and examines a set of seventeen conservation measures to be implemented during construction and operation of ANGP to minimize adverse impacts on caribou herds. These conservation measures can be used as a baseline for future developments on the North Slope to promote caribou herd management.