Enhancing Software Testing Using AI and Graph Similarity

Software testing plays a vital role in the development lifecycle, ensuring the prevention of failures and the enhancement of software quality. Despite its importance, the testing phase is often resource-intensive, involving numerous test cases that can become redundant or overlapping over time-leading to increased complexity and prolonged testing durations. To address these inefficiencies, this paper proposes a novel approach that integrates graph similarity analysis with generative AI and deep learning to optimize test suites. By leveraging call graphs derived from test cases, the method identifies redundant and closely related test scenarios. A machine learning model is used to predict similarity scores between these call graphs, facilitating the classification and prioritization of test cases. Lower similarity scores correspond to test cases with more unique code coverage and are thus assigned higher priority. This prioritization enables test engineers to focus on a more diverse and effective subset of test cases, ensuring thorough code coverage while improving efficiency. The proposed framework ultimately reduces redundancy, lowers testing costs, and upholds high standards of software quality, offering a systematic solution for determining the optimal level of testing required to meet study objectives. While the current study experimentally validates the use of graph similarity metrics for test case prioritization, the application of generative AI models is proposed as part of future extensions

Clinimetric Properties and Patient Group Validity of The Chicago-Quick Hand Function Test

This proposal aims to explore the clinimetric properties of the newly developed Chicago- Quick Hand Function Test (C-QHFT), a performance-based outcome measure (PBOM) designed to comprehensively assess hand function. Despite the availability of several PBOMs, current tests often fail to include key components such as in-hand manipulation (IHM) and psychomotor skills, limiting their effectiveness in evaluating hand function comprehensively. The C-QHFT incorporates various hand function components, including grasp, four IHM components, fine motor coordination (FMC), dexterity, release, and psychomotor skills, and has demonstrated strong psychometric properties in healthy adults. However, it has not yet been validated in a patient population. The study will employ a quasi-experimental quantitative design to assess the known group validity of the C-QHFT in adult patients with hand impairments. It will also determine the minimal clinically important difference (MCID), minimal detectable change (MDC), and the floor and ceiling effects. Participants will include adults receiving outpatient hand therapy. The study aims to compare C-QHFT scores between healthy adults and patients with hand impairments, establish an impairment scale, and further validate the tool’s clinical utility. The findings will contribute to the refinement of hand function assessments in clinical settings

The Use of GenAI in Graph Based Unit Testing

Software testing verifies that the software is free of defects and meets its requirements. This process includes various levels, one of which is unit testing, where developers create test cases alongside their regular code, and use frameworks, such as JUnit for Java, to enable a frequent automated execution of these test cases. However, designing test cases remains a significant challenge. Graph-based testing offers a solution by representing units in the source code as graphs, with nodes representing basic code blocks and edges representing transitions or interactions between these nodes. Additionally, modern Generative AI (GenAI) models, including ChatGPT, Gemini, and Copilot, present new opportunities for enhancing the software testing process. This paper investigates the potential of using GenAI models to automate and improve unit testing, particularly through graph-based methods. Experiments are designed to evaluate these models, assessing their ability to reduce manual effort while improving test coverage, efficiency, and code quality. The results reveal that GenAI models can streamline test generation and execution, but their effectiveness heavily relies on prompt quality and they lack an inherent understanding of program logic. In contrast, traditional graph-based unit testing ensures comprehensive coverage through systematic exploration of control flow paths but is resource-intensive. AQ1 Therefore, this paper recommends a hybrid approach that combines the automation capabilities of GenAI with the rigor of traditional methods to achieve robust and efficient software testing

Exploring the Impact of Pelvic Floor Health on Quality of Life in Women One to Ten Years Postpartum

Pelvic floor disorders are common among women, and it is projected that the number of American women with at least one pelvic floor disorder will be 43.8 million by 2050 (Weimer et al., 2024). Pelvic floor dysfunction impacts women beginning in early adulthood, and more women are impacted as age increases, with up to 50% of women over the age of 80 affected with pelvic floor dysfunction (Weimer, 2024). While all individuals are at risk of pelvic floor dysfunction, pregnant women are at a higher risk (Romeikiene & Daiva Bartkeviciene, 2021). The pelvic floor is a unique body system within females. This system controls bladder and bowel control, plays a role in postpartum recovery, and deals with urinary incontinence. When this system is damaged, it can create issues with physical activity, social participation, and engagement in sexual activity. For women in general, over time, this system can become weakened from childbirth, obesity, and constipation issues. Female pelvic floor dysfunction is treated by occupational therapists, physical therapists, medical doctors, or specialists such as urologists. Communication between healthcare providers and patients with pelvic floor dysfunction is a crucial aspect of client-centered care. Patients may not discuss symptoms or seek treatment with a care provider because they may not be knowledgeable about pelvic floor dysfunction and treatment or because they might wait to seek treatment until symptoms become severe (Burkhart, 2020). Patients are often hesitant to talk with care providers about the side effects of pelvic floor dysfunctions out of embarrassment (Grimes, 2023)

Menstrual Hygiene Management for Students with Intellectual Disabilities

Menstrual health management skills are important for participation in meaningful occupations, particularly for students with intellectual disabilities (ID). In Occupational Therapy, menstrual health management is an activity of daily living under the category of toilet and toilet hygiene. Occupational therapy can educate on these skills and can adapt to students’ understanding to promote the generalization of skills to manage their menstrual health. The aim of this research is to understand if adapted menstrual hygiene management intervention for students with ID will promote the acquisition of skills needed to manage menses. The investigators conducted a systematic review on this critically appraised topic through specific search terms and engines following inclusion criteria, such as an age range of 10-21, ID, and menstrual health management as a keyword. Four peer-reviewed journal articles within the last six years were selected after six were reviewed. Moderate quality evidence supports individualized and group menstrual hygiene management interventions such as demonstrating pad placement on dolls, peer training, social stories, and video modeling. More high-quality research on practical follow-ups of adapted interventions with this population is needed to determine the generalizability and application of menstrual health management skills longterm. Future research should be conducted to determine the benefits of occupational therapy’s role in increasing independence in menstrual health management for students with ID

Navigating difficult conversations and recognizing persons of concerns: Confrontation, de-escalation, and threat awareness

A student angry about their grade, a peer not pulling their weight, a supervisor sharing criticism; all can trigger anxiety and stress. Human beings experience physiological responses to stressful encounters that inhibit our ability to communicate, problem solve and listen when it’s most important to do so. Targeted attacks, like active shooters incidents, are not spontaneous, sudden events which occur without warning. They are predictable and, consequently, preventable. Students, co-workers or others may exhibit risk factors or observable behaviors that would indicate they may be on the “pathway to violence.” In this interactive presentation, participants will be introduced to methods to manage stress during a confrontation to remain intellectually competent to manage the encounter without succumbing to the instinctive visceral reactions that derail our rational responses. Several tools will be introduced for managing difficult conversations and confrontations. Participants will discover, through a self-assessment, their own personal conflict management style and understand how it affects their ability to collaborate toward reaching mutually positive outcomes. Additionally, this program will provide a basic understanding of the behavioral evolution of an attacker and help participants to recognize and respond to potential signs or cues that may indicate an individual is in distress, in need of help, or may be planning violence, and what interventions might help prevent an attack. Learning Objectives: Participants will gain insight into the natural physiological stress responses that affect cognitive capacity. Participants will learn skills to mitigate visceral responses to confrontation that inhibit problem solving. Participants will complete a self-assessment to determine their dominant conflict management style. Participants will learn and practice tools for effective de-escalation and confrontation. Participants will gain an understanding of basic threat assessment principles

Impact of Foreign Remittances, Foreign Direct Investment and Financial Development on Human Development of Selected Asian Countries

Foreign remittances play a contributing role in determining the growth potential of the nations of the world. Considering its significant role, the existing research has analyzed the major factors affecting the economic growth of some selected Asian nations. The data was utilized from 2005 to 2020 in some selected Asian countries. Human development was used as the dependent variable. However, foreign remittances, financial development and foreign direct investment, trade openness and labor force participation rate were taken as independent variables. The OLS regression results indicated that foreign remittances, foreign direct investment, and financial development led to enhanced nations\u27 human development. It was also found that trade openness and labor force participation also boosted the human development of the Asian economies. The findings suggested that the Government must focus on remittance inflow in concerned economies. These economies must have stable financial and political environments to attract more investment from foreign countries and have more production and human development. Finally, the Government should make credit facilities access and process very easy for the people of communities to increase investment, earnings, and economic growth