{"title":"CHECKR:用于输入记录数据验证的高效表驱动工具","authors":"S. R. White, J. Purdy","doi":"10.1145/1408800.1408857","DOIUrl":null,"url":null,"abstract":"It is desirable to detect and to identify properly any input data errors in a data collection system. The most common errors include hardware errors, field range errors, incorrect character-in-field errors, and records-out-of-sequence errors. In order to process these error conditions in a general manner, a set of Xerox FORTRAN and assembly language routines has been developed. These routines, collectively referred to as the CHECKR system, are table-driven and, therefore, can be used to validate input data from many different sources. A number of tables are created which specify the allowable conditions that can exist, and CHECKR uses these tables to produce an easy-to-read error message report. CHECKR has been used successfully to validate data for the Automated Data Repository (ADR) Project, a system to collect and process information concerning exercise and its relation to the prevention of coronary heart disease.","PeriodicalId":204185,"journal":{"name":"ACM '74","volume":"158 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"CHECKR: an efficient table-driven facility for input record data validation\",\"authors\":\"S. R. White, J. Purdy\",\"doi\":\"10.1145/1408800.1408857\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"It is desirable to detect and to identify properly any input data errors in a data collection system. The most common errors include hardware errors, field range errors, incorrect character-in-field errors, and records-out-of-sequence errors. In order to process these error conditions in a general manner, a set of Xerox FORTRAN and assembly language routines has been developed. These routines, collectively referred to as the CHECKR system, are table-driven and, therefore, can be used to validate input data from many different sources. A number of tables are created which specify the allowable conditions that can exist, and CHECKR uses these tables to produce an easy-to-read error message report. CHECKR has been used successfully to validate data for the Automated Data Repository (ADR) Project, a system to collect and process information concerning exercise and its relation to the prevention of coronary heart disease.\",\"PeriodicalId\":204185,\"journal\":{\"name\":\"ACM '74\",\"volume\":\"158 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACM '74\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/1408800.1408857\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM '74","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/1408800.1408857","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
CHECKR: an efficient table-driven facility for input record data validation
It is desirable to detect and to identify properly any input data errors in a data collection system. The most common errors include hardware errors, field range errors, incorrect character-in-field errors, and records-out-of-sequence errors. In order to process these error conditions in a general manner, a set of Xerox FORTRAN and assembly language routines has been developed. These routines, collectively referred to as the CHECKR system, are table-driven and, therefore, can be used to validate input data from many different sources. A number of tables are created which specify the allowable conditions that can exist, and CHECKR uses these tables to produce an easy-to-read error message report. CHECKR has been used successfully to validate data for the Automated Data Repository (ADR) Project, a system to collect and process information concerning exercise and its relation to the prevention of coronary heart disease.