Context

A dropship business model required special Guided Sales and Inventory behavior. DROPSHIP-SPECIAL products could be sold through Sales Order, but stock display was hardcoded and standard inventory movement had to remain unaffected.

QA Role

I mapped the special DROPSHIP-SPECIAL behavior across Guided Sales, API responses, product stock display, and inventory ledger records. I used Gherkin for repeatable rules and SQL checks to confirm that successful order creation did not create unintended stock movement.

Testing Scope

• Sales Order creation for DROPSHIP-SPECIAL products
• Hardcoded available stock display of 999.999
• Legal number prefix LEGAL-XXX
• Delivery date calculation from device date + 3 days
• Inventory ledger non-impact
• Invalid stock movement rejection
• Cross-module consistency between Guided Sales and Inventory

Test Approach

The primary risk was inconsistency: the Sales Order had to be created successfully while inventory remained untouched. Coverage therefore tested the successful order path, displayed stock behavior, stock ledger records, negative movement attempts, and database consistency.

Tools

Postman, MySQL, Jira, and Google Drive.

Methods & Formats

Gherkin / BDD.

Project Evidence Set

Test Case

Project-specific cases for DROPSHIP-SPECIAL order creation, hardcoded stock display, and inventory non-impact.

API Testing

Request and response validation for Sales Order creation, stock display, inventory ledger, and invalid movement attempts.

SQL Validation

Database checks confirming the order exists while standard inventory remains unaffected.

Gherkin / BDD

Business-readable scenarios for successful DROPSHIP-SPECIAL orders and intentional inventory non-impact.

Bug Report

Reproducible finding for incorrect inventory deduction after DROPSHIP-SPECIAL order creation.

Traceability Matrix

Mapping of DROPSHIP-SPECIAL rules to test cases, API checks, SQL validation, defects, and regression coverage.

Business Impact

The validation protected the intended dropship behavior: orders could proceed while inventory visibility and stock ledger data stayed consistent with the hardcoded non-impact rule.

Confidentiality

This case study reflects real QA responsibilities. Product rules, identifiers, and selected details have been generalized to protect confidential information.

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