Automated regression test fails after BOM change in stock control module

ERP SAP S/4HANA
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1

We have automated regression tests for our stock control module in SAP S/4HANA 2020 that run as part of our CI/CD pipeline. Recently, after updating a Bill of Materials (BOM) structure for one of our finished products, all related regression tests started failing.

The tests validate inventory calculations and material availability checks. The BOM version was updated to reflect new component quantities, but our test data wasn’t synchronized with this change. The automated tests still expect the old BOM structure and component quantities, so all assertions fail.

Test failure example:


Test: validate_material_availability
Expected component quantity: 5 units
Actual component quantity: 8 units
BOM version mismatch: Expected v1.2, Found v1.3

We’re struggling with BOM version management in our test scenarios. The test data alignment issue is blocking deployments because the pipeline marks these as critical failures. How should we handle BOM changes in automated regression testing to keep tests synchronized with evolving product structures?

2

BOM version management is tricky in automated testing because BOMs are living documents that change frequently in manufacturing environments. You need a strategy for either: 1) Parameterizing your tests to accept any valid BOM structure and validate logic rather than specific values, or 2) Implementing test data versioning that updates test expectations whenever BOMs change. The second approach requires a test data management tool that synchronizes with BOM changes in development.

3

I’ve dealt with this exact BOM regression testing challenge extensively. Here’s a comprehensive solution that addresses all three of your core issues:

Automated Regression Testing Strategy for BOM Changes:

The fundamental problem is that your tests are tightly coupled to specific BOM versions. You need to implement a flexible testing framework with multiple test categories:

Category 1: BOM-Agnostic Functional Tests (70% of your suite) These tests validate business logic without depending on specific BOM values:


Test: Material Availability Logic
1. Query current active BOM for material X
2. Calculate required components dynamically
3. Check if component availability >= required quantity
4. Validate availability check returns correct status

This approach tests the stock control logic regardless of BOM structure changes. Your test framework should:

  • Query the current BOM using CS_BOM_EXPL_MAT_V2 function module at test runtime
  • Calculate expected values based on current BOM data
  • Validate relationships rather than absolute values
  • Assert that business rules are followed (e.g., all components checked, correct availability status returned)

Category 2: BOM-Version-Specific Tests (20% of your suite) These tests validate specific scenarios with known BOM structures. Implement version-aware test data:


Test Data Structure:
- Material: TEST-FG-001 (Test Finished Good)
- BOM Version: REGRESSION-TEST-V1 (frozen)
- Components: TEST-COMP-A (qty: 5), TEST-COMP-B (qty: 3)
- Never modified in production systems

Create dedicated test materials with their own BOMs that are:

  • Used exclusively for regression testing
  • Documented as test data (marked with TEST- prefix)
  • Frozen and never updated
  • Maintained in a separate test data transport

Category 3: BOM Change Impact Tests (10% of your suite) These specifically test BOM version transitions:

  • Validate that changing BOM versions doesn’t break stock calculations
  • Test historical order processing with old BOM versions
  • Verify that stock control correctly handles multiple active BOM versions

BOM Version Management Implementation:

Your test framework needs BOM version awareness. Implement a test data manager class:

CLASS zcl_test_bom_manager DEFINITION.
  PUBLIC SECTION.
    METHODS:
      get_current_bom_version
        IMPORTING iv_material TYPE matnr
        RETURNING VALUE(rv_version) TYPE stlal,

      get_bom_components
        IMPORTING iv_material TYPE matnr
                  iv_version TYPE stlal
        RETURNING VALUE(rt_components) TYPE bom_comp_tab,

      calculate_expected_quantity
        IMPORTING iv_material TYPE matnr
                  iv_header_qty TYPE menge
        RETURNING VALUE(rt_expected) TYPE component_qty_tab.
ENDCLASS.

This manager class:

  • Queries current active BOM version from MAST/STKO tables
  • Retrieves component list with quantities from STPO
  • Calculates expected quantities based on current BOM structure
  • Provides test data that’s always synchronized with current BOMs

Test Data Alignment Solution:

Implement a three-tier test data strategy:

Tier 1: Dynamic Test Data Tests query production BOMs at runtime and calculate expected results dynamically. This eliminates synchronization issues but requires more complex test logic.

Tier 2: Versioned Test Data Maintain a test data repository that tracks BOM versions:


test_data_repo/
  materials/
    MAT-001/
      bom_v1.2.json  # Historical test data
      bom_v1.3.json  # Current test data
  expected_results/
    availability_check_v1.2.json
    availability_check_v1.3.json

When BOMs change in development:

  1. BOM change triggers webhook to test data repository
  2. Automated script exports new BOM structure
  3. Test data generator recalculates expected results
  4. Pull request created with updated test data
  5. QA team reviews and approves changes
  6. Regression tests use updated expectations

Tier 3: Frozen Test BOMs Create test-specific materials that never change, used for baseline regression tests that must remain stable.

Pipeline Integration:

Modify your CI/CD pipeline to handle BOM-sensitive tests:

stages:
  - name: Test Data Validation
    steps:
      - Check if BOMs changed since last test run
      - If changed, update dynamic test expectations
      - Validate test data repository is synchronized

  - name: Regression Tests - Dynamic
    steps:
      - Run BOM-agnostic tests (use current BOMs)
      - These tests query live BOM data

  - name: Regression Tests - Versioned
    steps:
      - Run tests against frozen test BOMs
      - Use TEST-* materials with stable structures

  - name: BOM Change Impact Analysis
    steps:
      - If BOMs changed, run additional validation
      - Compare results with previous version
      - Flag significant deviations for manual review

Addressing Your Specific Failure:

For your test that expects 5 units but finds 8 units:

Short-term fix: Update test data to match BOM v1.3


Expected component quantity: 8 units  # Updated
BOM version: v1.3  # Updated

Long-term solution: Refactor test to be BOM-version-independent


Test: validate_material_availability
1. Get current BOM version for material
2. Query component requirements from current BOM
3. expected_qty = current_bom.get_component_qty('COMP-X')
4. Assert actual_qty == expected_qty
5. Assert availability_status is_correct_for(actual_qty)

Best Practices for Stock Control Regression Testing:

  1. Separate test concerns: Don’t test BOM structure AND stock control logic in the same test
  2. Use test data builders: Create helper functions that generate test scenarios with current BOM data
  3. Tag BOM-dependent tests: Mark tests that rely on specific BOM versions so they can be handled differently
  4. Implement BOM change notifications: Alert test team when BOMs change so they can review impact
  5. Maintain test BOM documentation: Keep a registry of which test materials are used in which test scenarios

Implementing this multi-tiered approach will make your regression test suite resilient to BOM changes while maintaining comprehensive coverage of stock control functionality. The key is separating tests that validate business logic (BOM-agnostic) from tests that validate specific calculations (BOM-version-aware).

4

Your test data is hardcoded to specific BOM versions, which is fragile. Tests should either query the current active BOM version dynamically or use dedicated test BOMs that never change. We maintain separate test material masters with their own BOMs specifically for regression testing. These test materials are isolated from production changes and give us stable test scenarios.

5

Consider implementing BOM-agnostic test assertions. Instead of checking for specific component quantities, validate the logical relationships: “Does total component quantity match header quantity multiplied by BOM factor?” or “Are all required components available regardless of quantity?” This makes tests resilient to BOM changes while still validating business logic. You’re testing the stock control calculation engine, not the specific BOM structure.

6

From a test management perspective, you need to categorize your regression tests. Some tests should be BOM-version-specific (testing exact calculations with known inputs), while others should be BOM-agnostic (testing business rules and workflows). The BOM-specific tests should be tagged and automatically updated when BOMs change, or they should use frozen test BOMs. The BOM-agnostic tests should dynamically query current BOM data and validate proportional relationships rather than absolute values.

7

We solved this by creating a test data refresh pipeline that runs before regression tests. When a BOM changes in development, a hook triggers our test data update process. This process exports the new BOM structure, updates the test data repository, and regenerates expected test results based on the new BOM. The regression tests then run against current data. It requires initial setup effort but eliminates the synchronization problem you’re experiencing.