A self -testing approach for autonomic software

As researchers and practitioners move towards a vision of software systems that configure, optimize, protect, and heal themselves, they must also consider the implications of such self-management activities on software reliability. Autonomic computing (AC) describes a new generation of software systems that are characterized by dynamically adaptive self-management features. During dynamic adaptation, autonomic systems modify their own structure and/or behavior in response to environmental changes. Adaptation can result in new system configurations and capabilities, which need to be validated at runtime to prevent costly system failures. However, although the pioneers of AC recognize that validating autonomic systems is critical to the success of the paradigm, the architectural blueprint for AC does not provide a workflow or supporting design models for runtime testing. ^ This dissertation presents a novel approach for seamlessly integrating runtime testing into autonomic software. The approach introduces an implicit self-test feature into autonomic software by tailoring the existing self-management infrastructure to runtime testing. Autonomic self-testing facilitates activities such as test execution, code coverage analysis, timed test performance, and post-test evaluation. In addition, the approach is supported by automated testing tools, and a detailed design methodology. A case study that incorporates self-testing into three autonomic applications is also presented. The findings of the study reveal that autonomic self-testing provides a flexible approach for building safe, reliable autonomic software, while limiting the development and performance overhead through software reuse. ^

Menopause, Rurality, And Obesity in Rural African American Women

In the US, one in every eight deaths is due to an obesity-related chronic health condition (ORCHC). More than half of African American women (AAW) 20 years old or older are obese or morbidly obese, as are 63% of menopausal AAW. Many have ORCHC that increase their morbidity and mortality and increase health care costs. In 2013, 42.6 percent of AAs living in South Carolina (SC) were obese. The purpose of this cross-sectional study was to identify the cognitive, behavioral, biological, and demographic factors that influence health outcomes (BMI, and ORCHC) of AAW living in rural SC. A sample of 200 AAW (50 in each of the 4 groups of rurality by menopausal status), 18-64 years, completed the: Menopausal Rating Scale (symptoms); Body Image Assessment for Obesity (self-perception of body); Mental Health Inventory; Block Food Frequency Questionnaire; Eating Behaviors and Chronic Conditions, Traditional Food Habits, and Food Preparation Technique questionnaires – and measures for Body Mass Index. Most rural, and premenopausal AAW were single and not living with a partner. Premenopausal women had significantly higher educational levels. Sixty percent of AAW had between 1 and 5 ORCHC. Most AAW used salt based seasonings, ate deep fried foods 1 to 3 times a week, and ate outside the home 1 to 3 times a month. Few AAW knew the correct daily serving for grains and dairy, and most consumed less than the recommended daily serving of fruits, vegetables and dairy. Morbidly obese AAW used more traditional food preparation techniques than obese and normal-weight AAW. Rural, and menopausal AAW had significantly higher morbid obesity levels, consumed larger portions of meats and vegetables, and reported more body image dissatisfaction than very rural AAW, and premenopausal AAW, respectively. Controlling for socioeconomic factors the relationships between perceptions of body images, psychological distress, and psychological wellbeing remained significant for numbers of ORCHC