STATISTICAL ANALYSIS OF BIOLOGICAL TECHNIQUES, MOOD METRICS FOR ENHANCEMENT OF SOFTWARE QUALITY

Abstract- Software maintainability and dependability are critical for ensuring long-term success in software development projects. Traditional metrics like Lines of Code (LOC) and Cyclomatic Complexity have been widely used to assess these qualities, but they often fail to account for human factors, such as developer mood, which significantly impact productivity and code quality. This research explores the integration of biological techniques, including physiological and neurological measurements, with mood-augmented metrics to enhance software maintainability and dependability. By leveraging wearable devices, eye-tracking systems, and sentiment analysis, this study proposes a novel framework to correlate developer emotional states with software quality outcomes. The methodology involves a controlled experiment with 50 developers, analyzing their physiological data (heart rate, galvanic skin response) and mood indicators alongside traditional software metrics. Results indicate a significant correlation between positive mood states and improved maintainability, with a 15% reduction in defect density and a 20% increase in code readability. This paper discusses the implications of these findings and suggests future directions for integrating human-centric metrics into software engineering practices.