Datatype Conversion Scenario interview question in Cobol
Assume a Scenario:
You have an alphanumeric field X(10) that holds numeric data (but as characters), and you need to convert it to a numeric field 9(10).
In COBOL, the data types X(10) and 9(10) represent two different kinds of fields:
X(10): A string of 10 characters (alphanumeric data).
9(10): A numeric field with 10 digits.
Example:
X(10) (alphanumeric): '1234567890'
9(10) (numeric): 1234567890
To convert a data field from X(10) to 9(10), you are typically converting an alphanumeric string (which may contain numbers, letters, or special characters) into a purely numeric value. This conversion process will only work correctly if the alphanumeric data contains valid numeric characters (0-9), otherwise, it may result in an error or unexpected behavior.
*Steps to Convert in COBOL
->Define the Data Structures
DATA DIVISION. WORKING-STORAGE SECTION.
01 ALPHANUMERIC-FIELD PIC X(10). This is the X(10) field (alphanumeric)01 NUMERIC-FIELD PIC 9(10). This is the 9(10) field (numeric)Converting the Alphanumeric Value to Numeric:
PROCEDURE DIVISION.MOVE '1234567890' TO ALPHANUMERIC-FIELD Assign alphanumeric value*—>Convert ALPHANUMERIC-FIELD to NUMERIC-FIELDMOVE FUNCTION NUMVAL(ALPHANUMERIC-FIELD) TO NUMERIC-FIELD
DISPLAY 'Alphanumeric: ' ALPHANUMERIC-FIELD DISPLAY 'Numeric: ' NUMERIC-FIELDSTOP RUN.
* Function NUMVAL:
-> The NUMVAL function in COBOL is used to convert an alphanumeric string that contains only numeric characters into a numeric data type. If the string contains non-numeric characters (like letters or symbols), it will cause an error or produce unexpected results, so the data should be validated before attempting the conversion.
-> In this example, '1234567890' is a valid numeric string, so it is converted to the numeric field NUMERIC-FIELD successfully.
-> To convert an X(10) (alphanumeric) to a 9(10) (numeric), use the NUMVAL function in COBOL.Ensure that the alphanumeric field contains only numeric characters before conversion. You may need to validate or clean the data to avoid errors.