Designing a “software quality model” based on RCCA of defects and validating based on “quality algorithm”

Abstract

Software systems are very complex, and its complexity has grown exponentially as users' requirements and their usage have grown significantly. Users' requirements and the environment in which they use the software system keep changing, so maintaining its quality is very challenging. If the requirements of users are not met as per their expectations, they encounter defects that cause degradation of the quality of the software system. Such defects are analyzed to understand their impact, and they are fixed to help improve quality. In this research, a defect analysis technique called root cause and corrective actions (RCCA) is followed to analyzes different defect attributes, their interdependencies, and how they help in improving software system quality. The methodologies followed here are defining a hypothesis, finding a causal relationship between quality attributes, and testing the hypothesis. This research is based on quantitative or experimental research to understand the impact of theindependent variables on the dependent variable, which is software quality. This research identifies the “legacy quality score”, designs a new software system quality model, and quality algorithm to calculate the “new quality score”. The results indicate that the newly designed quality model helps improve the quality of the software system.