Abstract: This disclosure relates to a system and method for at source data masking and discovery of unique identifier for at-source masking. The method reads a table of production database comprising sensitive column from a source database for at source data masking. A unique identifier column is identified, and a temporary table is created which has three or more columns. Columns of temporary table comprises a sensitive column from the table of production database, a column for masked data of sensitive column and a unique identifier column. Sensitive column of the temporary table is masked using a known masking technique and the original data of the sensitive column and the masked data of the sensitive column is inserted into the temporary table. Finally, the production database is updated with the masked data of the sensitive column.

Abstract: This disclosure relates to a system and method for at source data masking and discovery of unique identifier for at-source masking. The method reads a table of production database comprising sensitive column from a source database for at source data masking. A unique identifier column is identified, and a temporary table is created which has three or more columns. Columns of temporary table comprises a sensitive column from the table of production database, a column for masked data of sensitive column and a unique identifier column. Sensitive column of the temporary table is masked using a known masking technique and the original data of the sensitive column and the masked data of the sensitive column is inserted into the temporary table. Finally, the production database is updated with the masked data of the sensitive column.

Abstract: System and method for cheque image data masking are disclosed. In an example, a cheque image and a data file are received, the data file includes data records with values corresponding to sensitive data fields in the cheque image. Further, a template cheque image matching to the cheque image and redacted information associated with the template cheque image are obtained. Furthermore, a blank image snippet is generated for each sensitive data field in the cheque image based on a part of the obtained information about sensitive fields. Moreover, values corresponding to each sensitive field from the input data file are written to the blank image snippet based on the remaining information about sensitive fields. Also, the template cheque image is updated with the image snippet. Data of non-sensitive fields in the cheque image is then copied to the template cheque image, thereby facilitating cheque image data masking.

Abstract: System and method for cheque image data masking are disclosed. In an example, a cheque image and a data file are received, the data file includes data records with values corresponding to sensitive data fields in the cheque image. Further, a template cheque image matching to the cheque image and redacted information associated with the template cheque image are obtained. Furthermore, a blank image snippet is generated for each sensitive data field in the cheque image based on a part of the obtained information about sensitive fields. Moreover, values corresponding to each sensitive field from the input data file are written to the blank image snippet based on the remaining information about sensitive fields. Also, the template cheque image is updated with the image snippet. Data of non-sensitive fields in the cheque image is then copied to the template cheque image, thereby facilitating cheque image data masking.

Abstract: The present subject matter relates a testing system for an application. The system includes a test data generation module to generate test data for a program code. The test data generation module in turn includes a relational expression creation module that determines a relational expression corresponding to a set of parameters of the program code based on a rule indicating a format of a valid test data for the parameters. A boundary recognition module identifies a set of boundary values of the parameters based on the relational expression. Further, a solver module then generates valid test data and invalid test data for the parameters based on the boundary values.

Abstract: Systems and methods for test data generation are described. In one implementation, the method includes receiving seed data having one or more characteristics. Further, the method includes obtaining a selection criterion indicating a selected portion of the seed data to be transformed. Based on the selection criterion, the seed data is transformed for at least a plurality of iterations to generate test data. The test data comprise a plurality of data sets including a primary data set generated in a first iteration and a secondary data set generated in each subsequent iteration. The primary data set includes transformed data corresponding to the selected portion of the seed data and non-transformed data corresponding to a remaining portion of the seed data and each secondary data set includes transformed data corresponding to the selected portion of the seed data.

Abstract: Systems and methods for test data generation are described. In one implementation, the method includes receiving seed data having one or more characteristics. Further, the method includes obtaining a selection criterion indicating a selected portion of the seed data to be transformed. Based on the selection criterion, the seed data is transformed for at least a plurality of iterations to generate test data. The test data comprise a plurality of data sets including a primary data set generated in a first iteration and a secondary data set generated in each subsequent iteration. The primary data set includes transformed data corresponding to the selected portion of the seed data and non-transformed data corresponding to a remaining portion of the seed data and each secondary data set includes transformed data corresponding to the selected portion of the seed data.

Abstract: The present subject matter relates a testing system for an application. The system includes a test data generation module to generate test data for a program code. The test data generation module in turn includes a relational expression creation module that determines a relational expression corresponding to a set of parameters of the program code based on a rule indicating a format of a valid test data for the parameters. A boundary recognition module identifies a set of boundary values of the parameters based on the relational expression. Further, a solver module then generates valid test data and invalid test data for the parameters based on the boundary values.