Writing effective API test cases ensures proper validation of an API’s functionality, security, and performance. Here’s a structured approach: 1. Understand API Requirements Before writing test cases, analyze API documentation to understand: Endpoints, request methods (GET, POST, PUT, DELETE) Request parameters and expected responses Authentication and authorization mechanisms 2. Define Test Scenarios Identify key scenarios,… Continue reading How to Write Effective Test Cases for API Testing
Author: Athul Narayanan
Top API Testing Tools: Postman, SoapUI, and Beyond
API testing is crucial for ensuring the reliability of software applications. Various tools help testers automate and validate API functionality. Here are some of the top API testing tools: 1. Postman One of the most popular API testing tools, Postman offers an intuitive interface for sending requests and analyzing responses. Supports REST, SOAP, and GraphQL… Continue reading Top API Testing Tools: Postman, SoapUI, and Beyond
Common HTTP Status Codes and Their Meaning in API Testing
In API testing, HTTP status codes indicate the success or failure of a request. Understanding these codes helps testers identify issues and ensure proper API behavior. 1xx: Informational 100 Continue – The server received the request and is waiting for the rest. 101 Switching Protocols – The server is switching protocols as requested. 2xx: Success… Continue reading Common HTTP Status Codes and Their Meaning in API Testing
REST vs. SOAP APIs: Key Differences for Testers
In API testing, two major protocols dominate: REST (Representational State Transfer) and SOAP (Simple Object Access Protocol). Understanding their differences helps testers design effective strategies. REST API REST is an architectural style that uses HTTP methods (GET, POST, PUT, DELETE) to interact with resources. It is stateless, meaning each request is independent. REST APIs are… Continue reading REST vs. SOAP APIs: Key Differences for Testers
API Testing vs UI Testing
When testing software, both API testing and UI testing play critical roles in ensuring a system works as expected. While UI testing focuses on the user interface, API testing ensures that the backend logic and data processing function correctly. Ignoring either one can lead to missed bugs, poor performance, or an inconsistent user experience. Let’s… Continue reading API Testing vs UI Testing
The Hidden Risks of Test Data
Test data plays a critical role in software testing, yet it is often overlooked. Many testers assume that as long as the test cases pass, the application works fine—but what if the data itself is flawed? Poor test data can lead to false positives, missed defects, and unreliable software. Let’s explore the hidden risks of… Continue reading The Hidden Risks of Test Data
Testing in the Dark: What If You Had No Requirements
Software testers rely on well-defined requirements to guide their testing process. But what happens when there are no requirements? No documentation, no acceptance criteria, and no clear expectations from stakeholders—just an application that needs to be tested. This situation is more common than it seems. Here’s how testers can approach requirement-less testing and still ensure… Continue reading Testing in the Dark: What If You Had No Requirements
UI Bugs That Only a Human Can Catch
Automation testing helps in many ways, but it cannot detect all UI issues. Some bugs require human observation and real-time interaction. Here are some UI bugs that automation often misses but manual testers can identify. 1. Overlapping Elements & Layout Issues Some elements like buttons or text fields overlap, making them unreadable. This usually happens… Continue reading UI Bugs That Only a Human Can Catch
Improving test coverage by 50%
Improving test coverage by 50% requires a strategic approach, focusing on identifying gaps, optimizing test cases, and leveraging automation. Here’s how we achieved it: 1. Analyzing Existing Coverage Used Code Coverage Tools: We utilized tools like JaCoCo (Java), Istanbul (JavaScript), and Coverage.py (Python) to measure code coverage. Reviewed Test Case Effectiveness: We assessed existing test… Continue reading Improving test coverage by 50%
How to Handle Flaky Tests in Automation
Handling flaky tests in automation is crucial for maintaining reliable test suites. Flaky tests produce inconsistent results, passing and failing intermittently without any actual changes in the code. Here’s how to handle them effectively: 1. Identify the Root Cause Run Tests Multiple Times: Execute the test multiple times to confirm its flakiness. Analyze Logs and… Continue reading How to Handle Flaky Tests in Automation