Third-party model software testing involves and generates large amounts of model software quality data. Currently, there is a deficiency in the collection, analysis and application of these data. Due to the characteristics of model software products (e.g., they are complex, uncertain and difficult to measure) as well as the limited and unsystematic understanding of model software quality, model software quality evaluation has always been a challenge in software quality research. Based on the features of third-party model software testing as well as the model software quality data collected during third-party testing, this study focuses on an in-depth analysis of defect data collected during model software testing by using the Pearson product-moment correlation coefficient, presents corresponding conclusions derived from the analysis of model software defect data, presents suggestions for software testing and evaluation organizations to scientifically manage model software quality data and improve software testing efficiency and provides quality control and improvement measures for software developers.
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