A compositional model for effort-aware just-in-time defect prediction on android apps
202202 bchy ; Version of Record ; Others ; This study was supported in part by the National Key Research and Development Project (No.2018YFB2101200), the National Natural Science Foundation of China (Nos.62002034, 62002306), the Fundamental Research Funds for the Central Universities (Nos.2020CDCGRJ072, 2020CDJQY-A021, and JUSRP121073), China Postdoctoral Science Foundation (No.2020M673137), the Special Funds for the Central Government to Guide Local Scientific and Technological Development (No.YDZX20195000004725), the Natural Science Foundation of Chongqing in China (No.cstc2020jcyj-bshX0114), the Key Project of Technology Innovation and Application Development of Chongqing (No.cstc2019jscx-mbdxX0020), HKPolyU Start-up Fund (No.ZVU7), CCF-Tencent Open Research Fund (No.ZDCK), and the European Commission grant (No.825,040) RADON. ; Early release
