What are the most common strategies for API integration testing?

I have experience with Spring Cloud Contract, but recently, I’ve come across a better idea for enterprise organizations. You can set up contract testing using a combination of OpenAPI specifications, GitHub and tools like Prism or Dredd for testing. 1. Create a GitHub repository to manage your Swagger/OpenAPI specifications. Store your API contract files (YAML/JSON) in this repository. 2. Prism: it is a tool that helps you mock your API based on your Swagger/OpenAPI specs. It allows you to simulate API responses for testing purposes. 3. Dredd: it is a testing tool that automates the testing of your API against its documentation. It reads your API blueprint (Swagger/OpenAPI) and performs tests based on the defined contracts.

Contract testing goes beyond traditional unit or integration testing, as it emphasizes the interactions between services or components.This can be immensely valuable in distributed systems where multiple teams or parties are involved, as it minimizes the potential for misunderstandings or misalignments in API usage. Contract tests rely heavily on accurate and up-to-date contracts. If the contract is incorrect or not updated to reflect changes in the API, it can lead to false negatives or missed issues. Maintaining contract accuracy can be challenging, especially in rapidly evolving systems.

As said E2E testing, you create an environment identical to the one that will be used by real users. Then you test all actions that your users might perform on your application.E2E testing also set disadvantages and challenges : 1)Testing the entire system with all its components, APIs, and integrations can lead to a significant testing burden. 2)Identifying the root cause of issues in end-to-end testing can be challenging. When a test fails, pinpointing the exact source of the problem can be time-consuming and may require extensive debugging In short E2E testing offers substantial benefits in assessing a system's functionality, usability, security, and performance, it is not without its drawbacks.

Mocking and stubbing thoroughly test each part of the system in isolation, making it easier to identify and address any issues specific to that component.By reducing the need to interact with external resources or services, mocking and stubbing can help lower the cost of testing.But they also have some limitation 1)They are not suitable for performance testing, load testing, or other tests that involve the evaluation of system scalability and efficiency. 2)It allow for isolated testing, they may not address interactions and integrations between different components or service 3)Handling real-time data or asynchronous operations can be challenging

Fuzz Testing for Banking Apps: Fuzz testing systematically inputs unexpected data, like special characters or unconventional values, to identify vulnerabilities and weaknesses in handling various inputs. This ensures robust security and stability for real-world scenarios, aiming to enhance the application's resistance to errors and overall reliability. ???? Key Objectives: Security Discovery: Fuzz testing uncovers and addresses banking application security vulnerabilities. Error Prevention: It detects and addresses potential errors or unexpected behaviors, ensuring robustness. Quality Assurance: Fuzz testing enhances software quality by simulating diverse scenarios beyond standard test cases.

Fuzz testing is particularly effective in uncovering vulnerabilities and defects that might go undetected through traditional testing methods. It has the ability to explore a broad range of inputs and scenarios, going beyond what developers might anticipate during traditional testing. But For applications where other aspects, such as user authentication and authorization, are more important, fuzz testing may not provide as much value.

It also comes with certain disadvantages and challenges:- 1)Executing a large number of test cases as part of regression testing can be time-consuming. T 2)Some tests may fail during regression testing not because of actual defects but due to changes in the environment or test conditions. Distinguishing between genuine failures and false positives can be challenging. 3)It is less effective for early-stage development when significant changes are still occurring.