API Chaining & End-to-End Flows

Practice complete real-time end-to-end API workflows.

Exercise 1: Login & Extract Token

  • Execute the Login API.
  • Extract the authentication token.

Exercise 2: Create a Resource

Create a resource and extract its unique ID.

Exercise 3: Fetch the Resource

Retrieve the resource using the extracted ID.

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Exercise 4: Update the Resource

Update the same resource using its ID.

Exercise 5: Validate the Updated Resource

Verify that all updates are reflected correctly.

Exercise 6: Delete the Resource

Delete the resource successfully.

Exercise 7: Validate Deleted Resource Access

Verify that the deleted resource behaves as expected when accessed again.

Exercise 8: Handle Chaining Failure

Validate behavior when one step in the chain fails.

Exercise 9: Handle Partial Failures

Practice handling partial failures.

Add retry logic where required.

Exercise 10: Execute the Complete End-to-End Flow

Run the complete workflow as a single automated test.

Exercise 11: Validate Data Consistency

Verify that data remains consistent across all APIs involved in the workflow.

Exercise 12: Debug Chaining Issues

Analyze failures occurring within chained API execution.

FakeStore Sprint-6 End-to-End Flow

Practice the complete sequence:

  • Login
  • Generate Token
  • Create User
  • Extract User ID
  • Create Product
  • Extract Product ID
  • Create Cart using User ID & Product ID
  • Fetch Cart
  • Update Cart
  • Delete Cart
  • Validate Complete End-to-End Flow

Also practice:

  • Chaining Failure Handling
  • Chaining Debugging

Core Skill

Extract values from one API response and pass them into subsequent API requests to automate complete business workflows.

Negative & Security Testing

Practice defensive API testing before production.

Exercise 1: Invalid Request Body

Send invalid request payloads.

Exercise 2: Missing Mandatory Fields

Validate mandatory-field validation.

Exercise 3: Invalid Data Types

Send incorrect data types.

Exercise 4: Empty Payload

Validate empty request bodies.

Exercise 5: Invalid Headers

Send incorrect request headers.

Exercise 6: Unauthorized Access

Validate:

  • 401 Unauthorized

responses.

Exercise 7: Forbidden Access

Validate:

  • 403 Forbidden

responses.

Exercise 8: Unsupported HTTP Method

Validate:

  • 405 Method Not Allowed

responses.

Exercise 9: SQL Injection Testing

Validate SQL Injection scenarios.

Exercise 10: XSS Testing

Validate Cross-Site Scripting (XSS) scenarios.

Exercise 11: Rate-Limit Testing

Verify API rate-limiting behavior.

Exercise 12: Large Payload Testing

Send excessive request payloads.

Exercise 13: Error Code Validation

Validate proper HTTP error codes.

Exercise 14: Error Response Validation

Verify:

Goal

Ensure APIs fail safely and predictably when receiving invalid input.

Validate:

  • Correct Error Codes
  • Consistent Error Messages
  • Proper Security Enforcement

Data-Driven Testing

Practice executing APIs using multiple datasets.

Exercise 1: Multiple Dataset Execution

Run the same API using:

Exercise 2: Validate Every Dataset

Verify responses for each iteration independently.

Exercise 3: Handle Partial Failures

Validate behavior when only some datasets fail.

Exercise 4: Validate Edge Cases

Execute edge-case datasets.

Exercise 5: Validate Boundary Values

Execute boundary-value datasets.

Exercise 6: Validate Bulk APIs

Run APIs with large datasets.

Exercise 7: Maintain Independent Test Data

Ensure test data remains isolated between executions.

Exercise 8: Reset Data

Restore application data after execution.

Exercise 9: Validate Data Accuracy

Verify:

  • API Data Accuracy
  • Report Accuracy

Exercise 10: Handle Dependent Data

Manage relationships between dependent datasets.

Exercise 11: Optimize Execution

Improve execution efficiency for large regression suites.

Purpose

Data-driven testing allows the same API to be validated across multiple datasets, users, edge cases, and boundary values.

Demo-API Mapping

API Chaining

Practice using:

  • reqres.in

Exercises include:

  • Login
  • Token Extraction
  • Create User
  • Extract User ID
  • Get User
  • Update User
  • Delete User
  • Validation

For multi-entity workflows, practice using:

  • fakestoreapi.com

Negative & Security Testing

Practice using writable demo APIs such as:

  • fakestoreapi.com
  • dummyjson.com

Exercises include:

  • Invalid Payloads
  • Missing Fields
  • Empty Payloads
  • Authentication Failures
  • SQL Injection
  • XSS
  • Unsupported HTTP Methods

Data-Driven Testing

Execute multiple datasets using:

  • CSV
  • Excel
  • JSON

Practice against:

  • reqres.in
  • dummyjson.com

FAQs

What Is API Chaining?

API chaining is the process of extracting values, such as authentication tokens or resource IDs, from one API response and passing them into subsequent API requests to automate complete business workflows.

How Do You Handle a Chaining Failure?

Practice:

  • Failure Handling
  • Partial Failure Handling
  • Retry Logic

Validate data consistency and debug the API that caused the failure.

Which Negative & Security Scenarios Should Be Tested?

Validate:

  • Invalid Payloads
  • Missing Fields
  • Empty Payloads
  • Invalid Headers
  • 401 Unauthorized
  • 403 Forbidden
  • 405 Method Not Allowed
  • SQL Injection
  • XSS
  • Rate Limiting
  • Large Payloads
  • Error Codes
  • Error Messages

What Is Data-Driven API Testing?

Execute the same API using multiple datasets from:

Validate every execution independently.

Why Should Test Data Remain Independent?

Independent test data prevents interference between executions.

Resetting test data after execution helps maintain stable regression results.