COBOL CORR and CORRESPONDING

Overview

The CORRESPONDING clause (abbreviated as CORR) in COBOL provides a powerful way to perform operations between group items where only fields with identical names are affected. This feature automatically matches fields by name and performs the specified operation only on those fields that exist in both groups, making it an efficient tool for bulk data manipulation and structure-to-structure operations.

CORRESPONDING is particularly valuable when working with similar data structures that may have evolved over time or when interfacing between different systems that use related but not identical record layouts. It eliminates the need to write individual MOVE, ADD, or SUBTRACT statements for each matching field, reducing code volume and maintenance overhead.

Understanding CORRESPONDING is essential for efficient COBOL programming, especially in environments where data structures are frequently modified or where you need to merge information from multiple sources with similar but not identical field layouts.

Basic MOVE CORRESPONDING

Simple Structure Mapping

The most common use of CORRESPONDING is with the MOVE statement to copy data between similar structures:

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01  INPUT-RECORD.
    05  CUSTOMER-ID         PIC 9(6).
    05  CUSTOMER-NAME       PIC X(30).
    05  CUSTOMER-ADDRESS    PIC X(50).
    05  PHONE-NUMBER        PIC X(15).
 
01  OUTPUT-RECORD.
    05  CUSTOMER-ID         PIC 9(6).
    05  CUSTOMER-NAME       PIC X(30).
    05  CUSTOMER-ADDRESS    PIC X(50).
    05  EMAIL-ADDRESS       PIC X(40).
 
MOVE CORRESPONDING INPUT-RECORD TO OUTPUT-RECORD.

In this example, MOVE CORRESPONDING will automatically move CUSTOMER-ID, CUSTOMER-NAME, and CUSTOMER-ADDRESS from INPUT-RECORD to OUTPUT-RECORD because these fields have matching names in both structures. PHONE-NUMBER and EMAIL-ADDRESS are ignored because they don't have corresponding matches.

Complex Nested Structures

CORRESPONDING works with nested group items, matching fields at any level within the hierarchy:

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01  EMPLOYEE-INPUT.
    05  PERSONAL-INFO.
        10  FIRST-NAME      PIC X(20).
        10  LAST-NAME       PIC X(25).
        10  BIRTH-DATE      PIC 9(8).
    05  WORK-INFO.
        10  DEPARTMENT      PIC X(10).
        10  SALARY          PIC 9(6)V99.
 
01  EMPLOYEE-OUTPUT.
    05  PERSONAL-DATA.
        10  FIRST-NAME      PIC X(20).
        10  LAST-NAME       PIC X(25).
        10  SSN             PIC 9(9).
    05  JOB-DATA.
        10  DEPARTMENT      PIC X(10).
        10  HIRE-DATE       PIC 9(8).
 
MOVE CORRESPONDING EMPLOYEE-INPUT TO EMPLOYEE-OUTPUT.

This operation will move FIRST-NAME, LAST-NAME, and DEPARTMENT to their corresponding fields in EMPLOYEE-OUTPUT, regardless of the different group names (PERSONAL-INFO vs PERSONAL-DATA, WORK-INFO vs JOB-DATA). The field names themselves determine the correspondence.

Data Type Conversion

MOVE CORRESPONDING automatically handles data type conversion between compatible fields:

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01  SOURCE-DATA.
    05  AMOUNT              PIC 9(5)V99.
    05  QUANTITY            PIC 9(4).
    05  DESCRIPTION         PIC X(30).
 
01  TARGET-DATA.
    05  AMOUNT              PIC 9(7)V99.
    05  QUANTITY            PIC 9(6).
    05  DESCRIPTION         PIC X(50).
 
MOVE CORRESPONDING SOURCE-DATA TO TARGET-DATA.

The MOVE CORRESPONDING operation will handle the size differences automatically, padding or truncating as necessary according to standard COBOL conversion rules. AMOUNT will be moved with proper decimal alignment, QUANTITY will be zero-filled on the left, and DESCRIPTION will be space-filled on the right.

Arithmetic CORRESPONDING Operations

ADD CORRESPONDING

ADD CORRESPONDING allows you to add corresponding numeric fields from one group to another:

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01  MONTHLY-SALES.
    05  PRODUCT-A-SALES     PIC 9(6)V99.
    05  PRODUCT-B-SALES     PIC 9(6)V99.
    05  PRODUCT-C-SALES     PIC 9(6)V99.
    05  COMMISSION          PIC 9(4)V99.
 
01  QUARTERLY-TOTALS.
    05  PRODUCT-A-SALES     PIC 9(8)V99.
    05  PRODUCT-B-SALES     PIC 9(8)V99.
    05  PRODUCT-C-SALES     PIC 9(8)V99.
    05  COMMISSION          PIC 9(6)V99.
    05  BONUS               PIC 9(4)V99.
 
ADD CORRESPONDING MONTHLY-SALES TO QUARTERLY-TOTALS.

This operation will add the monthly sales figures to the quarterly totals for all corresponding fields. PRODUCT-A-SALES, PRODUCT-B-SALES, PRODUCT-C-SALES, and COMMISSION will be added to their corresponding fields in QUARTERLY-TOTALS. The BONUS field is unaffected because it has no corresponding field in MONTHLY-SALES.

SUBTRACT CORRESPONDING

SUBTRACT CORRESPONDING works similarly to ADD, subtracting corresponding numeric fields:

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01  BUDGET-AMOUNTS.
    05  SALARY-BUDGET       PIC 9(7)V99.
    05  SUPPLY-BUDGET       PIC 9(6)V99.
    05  TRAVEL-BUDGET       PIC 9(5)V99.
    05  TRAINING-BUDGET     PIC 9(5)V99.
 
01  ACTUAL-EXPENSES.
    05  SALARY-BUDGET       PIC 9(7)V99.
    05  SUPPLY-BUDGET       PIC 9(6)V99.
    05  TRAVEL-BUDGET       PIC 9(5)V99.
    05  EQUIPMENT-COST      PIC 9(6)V99.
 
SUBTRACT CORRESPONDING ACTUAL-EXPENSES FROM BUDGET-AMOUNTS.

This operation subtracts the actual expenses from the budget amounts for all corresponding fields, effectively calculating the remaining budget. EQUIPMENT-COST is ignored because it has no corresponding field in BUDGET-AMOUNTS, and TRAINING-BUDGET remains unchanged because it has no corresponding field in ACTUAL-EXPENSES.

Mixed Data Types

When using arithmetic CORRESPONDING operations, non-numeric fields are automatically ignored:

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01  SALES-RECORD.
    05  SALESPERSON-NAME    PIC X(25).
    05  REGION-CODE         PIC X(5).
    05  CURRENT-SALES       PIC 9(6)V99.
    05  COMMISSION-RATE     PIC 9V99.
 
01  TOTALS-RECORD.
    05  SALESPERSON-NAME    PIC X(25).
    05  TERRITORY           PIC X(10).
    05  CURRENT-SALES       PIC 9(8)V99.
    05  COMMISSION-RATE     PIC 9V99.
 
ADD CORRESPONDING SALES-RECORD TO TOTALS-RECORD.

In this ADD CORRESPONDING operation, only CURRENT-SALES and COMMISSION-RATE will be added because they are numeric. SALESPERSON-NAME is ignored even though it has a corresponding field, because ADD operations only work with numeric data. REGION-CODE and TERRITORY don't correspond by name.

Tutorial: Building a Data Integration System

Let's create a comprehensive data integration system that demonstrates the power of CORRESPONDING operations for merging data from multiple sources with different but related structures. This tutorial will show you how to build a flexible system that can handle evolving data formats efficiently.

Step 1: Define Source Data Structures

First, we'll establish different source data structures that represent the same basic information in slightly different formats:

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WORKING-STORAGE SECTION.
01  LEGACY-CUSTOMER-RECORD.
    05  CUSTOMER-ID         PIC 9(6).
    05  CUSTOMER-NAME       PIC X(30).
    05  STREET-ADDRESS      PIC X(40).
    05  CITY                PIC X(20).
    05  STATE               PIC X(2).
    05  ZIP-CODE            PIC 9(5).
    05  PHONE-NUMBER        PIC X(12).
    05  CREDIT-LIMIT        PIC 9(6)V99.
 
01  NEW-CUSTOMER-RECORD.
    05  CUSTOMER-ID         PIC 9(8).
    05  CUSTOMER-NAME       PIC X(50).
    05  STREET-ADDRESS      PIC X(60).
    05  CITY                PIC X(25).
    05  STATE               PIC X(2).
    05  ZIP-CODE            PIC 9(9).
    05  EMAIL-ADDRESS       PIC X(40).
    05  CREDIT-LIMIT        PIC 9(8)V99.
    05  LAST-UPDATE         PIC 9(8).

These structures represent customer data from legacy and new systems. While they have many fields in common, there are differences in field sizes and some unique fields. CORRESPONDING operations will help us merge this data efficiently.

Step 2: Create a Master Integration Structure

Next, we'll define a master structure that can accommodate data from all sources:

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01  MASTER-CUSTOMER-RECORD.
    05  CUSTOMER-ID         PIC 9(8).
    05  CUSTOMER-NAME       PIC X(50).
    05  STREET-ADDRESS      PIC X(60).
    05  CITY                PIC X(25).
    05  STATE               PIC X(2).
    05  ZIP-CODE            PIC 9(9).
    05  PHONE-NUMBER        PIC X(15).
    05  EMAIL-ADDRESS       PIC X(40).
    05  CREDIT-LIMIT        PIC 9(8)V99.
    05  LAST-UPDATE         PIC 9(8).
    05  DATA-SOURCE         PIC X(10).
    05  INTEGRATION-FLAGS.
        10  PHONE-AVAILABLE     PIC X(1).
        10  EMAIL-AVAILABLE     PIC X(1).
        10  ADDRESS-VERIFIED    PIC X(1).

The master structure includes all possible fields from both source systems, with sizes large enough to accommodate the largest values. Additional fields track data source and availability flags to manage the integration process.

Step 3: Implement Legacy Data Integration

Now we'll create the logic to integrate legacy customer data:

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INTEGRATE-LEGACY-CUSTOMER.
    INITIALIZE MASTER-CUSTOMER-RECORD
    
    MOVE CORRESPONDING LEGACY-CUSTOMER-RECORD 
         TO MASTER-CUSTOMER-RECORD
    
    MOVE 'LEGACY' TO DATA-SOURCE
    MOVE 'Y' TO PHONE-AVAILABLE
    MOVE 'N' TO EMAIL-AVAILABLE
    MOVE 'N' TO ADDRESS-VERIFIED
    
    IF PHONE-NUMBER NOT = SPACES
        MOVE 'Y' TO PHONE-AVAILABLE
    END-IF
    
    PERFORM VALIDATE-CUSTOMER-DATA
    PERFORM WRITE-MASTER-RECORD.

This integration routine uses MOVE CORRESPONDING to automatically copy all matching fields from the legacy record to the master record. Additional logic sets integration flags and handles data source identification. The CORRESPONDING operation eliminates the need to code individual MOVE statements for each field.

Step 4: Implement New System Data Integration

Let's create similar logic for the new system data with different processing rules:

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INTEGRATE-NEW-CUSTOMER.
    INITIALIZE MASTER-CUSTOMER-RECORD
    
    MOVE CORRESPONDING NEW-CUSTOMER-RECORD 
         TO MASTER-CUSTOMER-RECORD
    
    MOVE 'NEW_SYS' TO DATA-SOURCE
    MOVE 'N' TO PHONE-AVAILABLE
    MOVE 'Y' TO EMAIL-AVAILABLE
    MOVE 'Y' TO ADDRESS-VERIFIED
    
    IF EMAIL-ADDRESS NOT = SPACES
        MOVE 'Y' TO EMAIL-AVAILABLE
    END-IF
    
    IF LAST-UPDATE = ZERO
        MOVE FUNCTION CURRENT-DATE(1:8) TO LAST-UPDATE
    END-IF
    
    PERFORM VALIDATE-CUSTOMER-DATA
    PERFORM WRITE-MASTER-RECORD.

The new system integration follows a similar pattern but with different business rules. The MOVE CORRESPONDING operation works identically, automatically handling the field mapping regardless of the source system differences.

Step 5: Implement Data Consolidation

Finally, we'll create logic to consolidate data from multiple sources for the same customer:

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CONSOLIDATE-CUSTOMER-DATA.
    READ MASTER-FILE INTO EXISTING-CUSTOMER-RECORD
    
    IF CUSTOMER-ID = EXISTING-CUSTOMER-ID
        PERFORM MERGE-CUSTOMER-INFORMATION
    ELSE
        PERFORM WRITE-NEW-CUSTOMER-RECORD
    END-IF.
 
MERGE-CUSTOMER-INFORMATION.
    IF EMAIL-ADDRESS = SPACES AND 
       EXISTING-EMAIL-ADDRESS NOT = SPACES
        MOVE EXISTING-EMAIL-ADDRESS TO EMAIL-ADDRESS
        MOVE 'Y' TO EMAIL-AVAILABLE
    END-IF
    
    IF PHONE-NUMBER = SPACES AND
       EXISTING-PHONE-NUMBER NOT = SPACES
        MOVE EXISTING-PHONE-NUMBER TO PHONE-NUMBER
        MOVE 'Y' TO PHONE-AVAILABLE
    END-IF
    
    IF CREDIT-LIMIT > EXISTING-CREDIT-LIMIT
        MOVE CREDIT-LIMIT TO EXISTING-CREDIT-LIMIT
    END-IF
    
    MOVE CORRESPONDING MASTER-CUSTOMER-RECORD 
         TO CONSOLIDATED-CUSTOMER-RECORD.

The consolidation logic merges information from multiple sources, filling in missing data and applying business rules for conflict resolution. MOVE CORRESPONDING is used in the final step to create the consolidated record efficiently.

Advanced CORRESPONDING Techniques

Conditional CORRESPONDING Operations

You can combine CORRESPONDING with conditional logic for more sophisticated data processing:

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PROCESS-CUSTOMER-UPDATE.
    IF UPDATE-TYPE = 'FULL'
        MOVE CORRESPONDING INPUT-CUSTOMER TO MASTER-CUSTOMER
    ELSE
        IF UPDATE-TYPE = 'PARTIAL'
            PERFORM SELECTIVE-UPDATE
        END-IF
    END-IF.
 
SELECTIVE-UPDATE.
    IF INPUT-CUSTOMER-NAME NOT = SPACES
        MOVE INPUT-CUSTOMER-NAME TO MASTER-CUSTOMER-NAME
    END-IF
    
    IF INPUT-PHONE-NUMBER NOT = SPACES
        MOVE INPUT-PHONE-NUMBER TO MASTER-PHONE-NUMBER
    END-IF
    
    ADD CORRESPONDING INPUT-AMOUNTS TO MASTER-AMOUNTS.

This approach allows you to use CORRESPONDING for bulk operations while maintaining fine-grained control over specific fields. The combination provides both efficiency and flexibility in data processing.

Error Handling with CORRESPONDING

Implement proper error handling when using CORRESPONDING operations, especially with arithmetic operations:

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SAFE-ADD-CORRESPONDING.
    MOVE ZERO TO WS-ERROR-COUNT
    
    ADD CORRESPONDING SOURCE-AMOUNTS TO TARGET-AMOUNTS
        ON SIZE ERROR
            ADD 1 TO WS-ERROR-COUNT
            PERFORM LOG-SIZE-ERROR
    END-ADD
    
    IF WS-ERROR-COUNT = ZERO
        PERFORM COMMIT-TRANSACTION
    ELSE
        PERFORM ROLLBACK-TRANSACTION
    END-IF.

Error handling ensures that arithmetic CORRESPONDING operations are performed safely, with appropriate recovery actions when size errors or other exceptions occur.

Performance Optimization

For high-volume processing, consider the performance implications of CORRESPONDING operations:

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* For frequently used operations, consider explicit moves
* when you know exactly which fields need to be processed
 
OPTIMIZED-CUSTOMER-COPY.
    IF FULL-COPY-REQUIRED
        MOVE CORRESPONDING SOURCE-CUSTOMER TO TARGET-CUSTOMER
    ELSE
        * Explicit moves for known critical fields
        MOVE SOURCE-CUSTOMER-ID TO TARGET-CUSTOMER-ID
        MOVE SOURCE-CUSTOMER-NAME TO TARGET-CUSTOMER-NAME
        MOVE SOURCE-CREDIT-LIMIT TO TARGET-CREDIT-LIMIT
    END-IF.

While CORRESPONDING is convenient, explicit field moves may be more efficient for high-frequency operations where you know exactly which fields need processing. Balance convenience with performance requirements based on your specific application needs.

Practical Exercises

Exercise 1: Employee Data Migration

Create an employee data migration system using CORRESPONDING operations:

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* Design structures for:
* - Old employee records (different field sizes)
* - New employee records (additional fields)
* - Temporary migration records
* Use CORRESPONDING to migrate data efficiently
* Handle field size differences and new fields
* Implement validation and error handling

Solution Approach: Create structures with overlapping field names but different sizes. Use MOVE CORRESPONDING for bulk migration, then add specific logic for new fields and validation. Include error handling for size overflow and data conversion issues.

Exercise 2: Financial Report Consolidation

Build a financial report consolidation system with multiple data sources:

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* Implement consolidation for:
* - Monthly departmental reports
* - Quarterly divisional summaries  
* - Annual company totals
* Use ADD CORRESPONDING for accumulation
* Handle different reporting periods
* Include variance calculations and analysis

Solution Approach: Create hierarchical structures with matching field names for different reporting levels. Use ADD CORRESPONDING to accumulate totals efficiently. Implement period validation and variance analysis using SUBTRACT CORRESPONDING operations.

Exercise 3: Inventory System Integration

Design an inventory integration system for multiple warehouse systems:

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* Create integration for:
* - Different warehouse management systems
* - Varying product code formats
* - Multiple inventory tracking methods
* Use CORRESPONDING for data normalization
* Implement product matching algorithms
* Handle quantity and value consolidation

Solution Approach: Design flexible structures that can accommodate different warehouse formats. Use CORRESPONDING for initial data mapping, then implement specific logic for product code normalization and inventory consolidation. Include comprehensive validation and reconciliation procedures.

Best Practices and Guidelines

Structure Design

• Use consistent field naming conventions across related structures
• Design field sizes to accommodate the largest expected values
• Group related fields logically within structures
• Document which fields are intended to correspond between structures
• Consider future expansion when designing field layouts
• Use meaningful names that clearly indicate field purpose

Operation Selection

• Use MOVE CORRESPONDING for structure-to-structure copying
• Use ADD CORRESPONDING for accumulating totals and summaries
• Use SUBTRACT CORRESPONDING for variance analysis and adjustments
• Consider explicit moves for performance-critical operations
• Validate data types before arithmetic CORRESPONDING operations
• Test with various data combinations to ensure correct behavior

Error Handling and Validation

• Always include SIZE ERROR handling for arithmetic operations
• Validate field compatibility before CORRESPONDING operations
• Log any data conversion issues or truncation warnings
• Test with boundary values and edge cases
• Implement rollback procedures for failed operations
• Document expected behavior for non-corresponding fields

Maintenance and Documentation

Maintain clear documentation of which fields are expected to correspond between structures. When modifying data structures, consider the impact on existing CORRESPONDING operations. Field name changes can break correspondence relationships, so plan changes carefully and update all affected code.

Regular review of CORRESPONDING operations ensures they continue to work as intended as data structures evolve. Include CORRESPONDING operations in your testing strategy, particularly when field layouts change or new fields are added to existing structures.

Interactive Quiz