Abstract: As being the infrastructure of prediction model's construction and implementation,software defect prediction dataset faces two sets of problems.On the one hand,due to the difficulty of data collection from data sources,there are fewer available datasets.On the other hand,due to the difference of data in diverse fields and the inapplicability of software metrics standards,the published datasets are rarely applied in engineering.In this paper,combined with the real software testing data in the domestic space field,the method of spacecraft software metrics design and the construction process of spacecraft software defect prediction dataset are systematically expounded.According to the characteristics of the spacecraft software,a hybrid method combining the metrics based on code and quality of the software is proposed to ensure that the relevant characteristics of the spacecraft software can be described and measured comprehensively from different angles.At the same time,to solve the problem of high labor and storage cost for large-scale data collection,processing and analysis,a standardized dataset construction method combining the data cleaning process under version division and module hierarchical preprocessing is proposed.The dataset SPACE constructed based on this method is demonstrated,which proves that the method can be effectively applied to the construction of domain-specific high-quality software defect prediction dataset,and at the same time,good prediction effect of model AutoWeka can be obtained.

Key words: Data quality, Dataset, Software defect prediction, Software metrics, Spacecraft software