June 12, 2023
14 min read

Guide to API Testing: Understanding the Basics

Adam Bauman

APIs come in many different shapes and sizes and have been around for a long time. Whether you are brand new to the topic or think about your day-to-day in terms of RESTful methods, you are using APIs every day.

"This morning I PUT on my clothes, went to the kitchen to GET a cup of coffee, sat at my computer and felt the satisfaction of finding emails to DELETE that don't need any action from me. My morning ended up being pretty 200 OK."

Any developer will tell you that testing is a very important part of creating world-class software. They will also tell you that they were on a tight deadline and they had to skip writing tests. But don't worry, their code is "rock solid". In this post we'll start with the definition of an API and walk through some reasons you should test your APIs. Then we'll talk about why it's important to test your APIs and share some tips on how to use modern tools to help automate the process.

Let's dive in!

Definition of an API

An API, Application Programming Interface, is like a waiter who takes orders from one application and delivers it to another. It's the backbone of many modern software applications, connecting various components to ensure that everything runs smoothly. But like a waiter, APIs can sometimes make mistakes, which is why it's important to test them thoroughly.

What is API Testing?

When it comes to ensuring optimum performance of APIs, testing is undoubtedly essential. It involves verifying not only functionality but also the API’s security levels and ability to perform well under pressure. Thorough API tests entails sending requests to an endpoint followed by analyzing its respective response(s). The results confirm if indeed the API operates in compliance with specific requirements; returns predicted information while also managing errors efficiently.

A good friend of mine stole a quote from a famous philosopher and loves to use it whenever we are talking about how to ensure the quality of the software we are creating:

"Quality is not an act, it’s a habit" – Aristotle

This starts with solid requirements and extends through the creation of automated testing of your software. APIs are no exception, in fact, they are probably more important to test since the primary consumer of your APIs will be other developers who depend on the stability of your application.

Long gone are the days where manual testing was the primary method for ensuring code quality. Automated testing now rules the landscape and building your tests into deployment pipelines will save a lot of time (which business leaders also call "money") and free you up to work on new, exciting applications rather than an endless queue of bugs to fix. It's not a silver bullet to solve all quality issues but the more you automate the easier your life will be.

Some popular tools for API testing include Insomnia, Postman, SoapUI, and Selenium. These tools allow you to test your API endpoints, automate your testing process, and generate reports to help you analyze your results.

So, whether you’re creating a new application, managing an existing application, or keeping the lights on for a legacy application, testing your API is essential.

API Documentation

The holy grail of any API is to be so intuitive that no documentation is needed. Unfortunately, Indiana Jones isn't available for most developers so the Holy Grail remains elusive so we need to make sure all of our APIs are well documented. This includes both internal and external APIs.

Documenting your API is crucial because it helps other developers understand how to use it effectively. It provides information on the different endpoints, input parameters, response formats, error messages, and API authentication requirements. By providing clear documentation, you enable other developers to integrate your API into their applications more quickly and with fewer errors. Well documented APIs can also help reduce the number of support requests you receive from developers who are struggling to use them.

Protect Mission-Critical APIs & Services: Efficient protection strategies revealed

What Are The Different Types of API Testing?

Just like our waiter friend that is delivering food from the kitchen to our table, there are many different things that can happen by mistake. Your food could take too long to get to your table and be cold ("meal latency"), someone else could get food meant for you ("meal-in-the-middle attack"). So there are many approaches that you can take to ensure your APIs are doing what they are supposed to do at scale and are as protected as possible from bad actors.

Functional Testing

Does the code do what it's supposed to do? This is where robust requirements and techniques like Test Driven Development (TDD) are your friend. As a developer, you can only test for what you are told the software is supposed to achieve. Functional testing is a form of testing that concentrates on confirming an API's functionality aligns with its defined requirements and anticipated behavior. It consists of assessing the API's functionality through sending requests to its endpoints and confirming the responses match predefined expected results. The key objective of functional testing is to guarantee the API operates accurately and produces the anticipated outcomes across different input situations. This encompasses evaluating the API's key functionalities, unusual scenarios, error management, and adherence to business regulations and demands.

Positive Testing

Positive testing is also referred to as "happy path" testing. It involves testing the API using valid inputs and expected conditions to confirm that it operates correctly and produces the anticipated results. The main goal of this testing approach is to validate that the API performs as expected when given valid data and scenarios. During positive testing, the tester confirms the correct functioning of the API with valid inputs and expected conditions. This encompasses testing different valid input parameters, headers, authentication tokens, and data formats. The objective of positive testing is to ascertain that the API satisfies its functional specifications and generates the expected outcomes for valid scenarios.

Negative Testing

Negative testing is the antithesis of positive testing. It encompasses testing the API using invalid inputs, unforeseen conditions, or extreme cases to verify the API's ability to manage errors and exceptions effectively. The objective is to ascertain and confirm how the API reacts to flawed data, boundary situations, or unexpected circumstances, ensuring it remains stable without generating unexpected outcomes. Negative testing entails evaluating the API with inappropriate, malformed, or unforeseen inputs to guarantee it manages errors and exceptions smoothly. This comprises assessing scenarios like missing or inaccurate parameters, incorrect data structures, unauthorized access trials, and other instances that stray from the anticipated input. The aim is to authenticate the API's error management, security protocols, and its capacity to manage and report errors proficiently without crashing or revealing sensitive data.

Boundary Value Testing

Boundary value testing is centered around evaluating the API's performance at the limits or edges of acceptable input ranges. It entails assessing the API using input values at the lowest, highest, and slightly beyond or below the specified limits. This testing approach is instrumental in pinpointing flaws or unanticipated outcomes that could arise at the peripheries of valid input ranges.

Equivalence Partitioning

Equivalence partitioning involves dividing an API's input data into partitions or equivalence classes, where inputs within the same partition yield identical outputs. By testing representative inputs from each equivalence class instead of every possible input value, this technique effectively reduces the number of test cases while ensuring comprehensive API coverage.

Non-Functional Testing

Non-functional API testing involves evaluating the non-functional aspects of an API, such as performance, security, reliability, and usability, to ensure it meets the necessary requirements and functions effectively in real-world situations. Conducting these tests is crucial for identifying issues and weaknesses before the API is launched, ultimately enhancing its quality and user experience.

Load Testing

Load testing assesses how an API performs under different levels of concurrent requests or simulated user loads, aiming to uncover bottlenecks, performance problems, and the maximum capacity it can handle before issues arise. Given that external applications typically call APIs, you lack control over their usage, leaving your application vulnerable to attacks, coding errors, and challenges when increased demand arises.

Performance Testing

A crucial element in a well-designed API is maintaining low latency. APIs are often a part of a larger process that serves a higher-level business purpose. The logic chain involved is usually intricate, and identifying weak points can be challenging when performance is affected. Monitoring the performance metrics of your APIs and observing any changes resulting from modifications made in the background will facilitate the prompt detection of bottlenecks. It is essential to distinguish between the latency within your application and any delays caused by external systems, such as upstream APIs. Performance testing, a form of non-functional testing, assesses an API's speed, responsiveness, and efficiency in various scenarios. This testing includes techniques like load testing, stress testing, and soak/endurance testing to evaluate the performance attributes of the API.

Stress Testing

Stress testing assesses an API's performance and stability under extreme conditions to determine its breaking point and reveal potential vulnerabilities or weaknesses. The API is deliberately strained beyond its limits by simulating high loads, limited resources, or other stressful scenarios to uncover issues like memory leaks and ensure error handling and recovery mechanisms are effective.

Scalability Testing

Scalability testing is a performance evaluation method that assesses the API's capacity to adjust to varying demand or workloads. It gauges the API's ability to manage fluctuations in traffic, user activity, and data volume without compromising performance. The testing process involves incrementally increasing or decreasing loads to mimic real-world scenarios, such as adjusting the number of users or data volume. The main goals of scalability testing include validating the API's performance under increased demand, identifying potential bottlenecks, determining the optimal infrastructure setup, and ensuring efficient scaling down when demand decreases.

Reliability Testing

Reliability testing assesses the API's consistent performance and dependability over an extended period under various conditions and workloads to identify and address potential issues like memory leaks, resource depletion, or performance decline. This type of testing involves subjecting the API to sustained loads over time to mimic real-world usage, monitoring its performance, resource usage, and stability. The main goals include confirming the API's long-term reliability, pinpointing and resolving stability issues, testing the API's ability to recover from failures, and ensuring consistent performance under sustained workloads. This testing is crucial for APIs expected to run continuously or handle critical workloads to prevent downtime or failures with significant repercussions.

Security Testing

The importance of securing your APIs is becoming more and more important as businesses adopt widespread use of APIs to exchange data both internally within the business and externally to partners and customers.

Authentication Testing

Authentication testing is centered on confirming the efficiency and strength of the authentication methods utilized by the API. This process includes evaluating different authentication protocols like API keys, JSON Web Tokens (JWT), OAuth, and conventional username/password pairs. The main goals of authentication testing are to ensure that only authorized users or clients can reach the API and its assets, validate the secure handling of authentication credentials, detect vulnerabilities like brute-force attacks, credential stuffing, and session management problems, and confirm the deployment of multi-factor authentication (MFA) systems if relevant.

Authorization Testing

Authorization testing, which is different than authentication, verifies that the API enforces correct access control and authorization rules according to user roles, permissions, and privileges. It includes testing situations where users or clients try to access or perform actions on resources they should not be able to access or modify. Key aspects of authorization testing encompass confirming that users can only interact with resources they are permitted to, checking for vulnerabilities that could lead to unauthorized access, enforcing data segregation based on user roles, and validating the implementation of least privilege and role-based access control.

Injection Attacks (SQL, XSS, XXE)

Injection attacks involve assessing the API's input validation and sanitization methods by testing them with different types of malicious input payloads, including SQL Injection, Cross-Site Scripting (XSS), and XML External Entity (XXE) vulnerabilities.

Data Exposure Testing

Data exposure testing aims to discover weaknesses that may result in the unintended exposure or release of confidential information like personally identifiable information (PII), credentials, or proprietary data. This involves checking for insecure direct object references (IDOR) enabling unauthorized access to resources, confirming that sensitive data is not mistakenly disclosed in error messages, logs, or other forms of output, guaranteeing that data is appropriately concealed when provided to unauthorized users or clients, and testing for information disclosure vulnerabilities that could expose system specifics or sensitive metadata.

Encryption Testing

Encryption testing is performed to validate the accurate implementation and use of encryption techniques to protect data while it is being transmitted and stored. The process includes ensuring that sensitive data is encrypted with strong encryption algorithms and appropriate key lengths, evaluating secure key management practices, confirming consistent encryption enforcement across communication channels and data storage, and preventing situations where encryption may be bypassed or disabled, potentially leading to data exposure.

Integration Testing

Integration testing is the process of testing how different components of an API work together to ensure they are functioning correctly. It involves testing the API's input and output as well as how it integrates with other components within the system. This is an often overlooked testing technique when developing APIs. Since your application is most likely relying on the APIs of other systems, it is critical that you know when they are unavailable or have changed in a way that you are not anticipating. I recommend that you set up tests (and alerts) on any external APIs that are part of your critical business workflows.

End-to-End Testing

End-to-end testing, also known as E2E testing, is an approach to testing an APIs integration and functionality within a system or application. It simulates real world scenarios by testing the API across stages, including its interactions with parts of the system, databases and external systems. The process involves setting up the test environment with all components verifying the APIs authentication and authorization processes, preparing test data, sending API requests with input data and parameters confirming responses ensuring data consistency. End-to-end testing is essential for identifying issues related to dependencies, data flow and component interactions that may be missed during unit testing.

Interoperability Testing

Checking interoperability ensures that the API can smoothly connect and interact with systems, platforms or coding languages. It confirms that the API adheres, to industry standards, protocols and data formats allowing it to function with a variety of client applications and services. This testing assesses how well the API merges with client applications or services developed using programming languages and frameworks. It also validates its compatibility with operating systems, hardware platforms and environments while ensuring it can manage data formats (like JSON, XML, Protocol Buffers) and communication protocols (such as HTTP, WebSockets, gRPC). Additionally it evaluates its ability to handle character encodings, locales, internationalization scenarios while confirming its support for authentication and authorization mechanisms required by client applications or services. Interoperability testing is crucial, for guaranteeing that the API can be seamlessly integrated and utilized by a range of clients and systems to enhance compatibility and simplify integration challenges.

Workflow Testing

Workflow testing is focused on validating end-to-end business processes and workflows involving multiple API interactions. It confirms the API's capability to manage intricate scenarios across various endpoints, data conversions, and conditional logic. The process includes identifying and outlining business processes and workflows related to the API, generating test scenarios to replicate these workflows through sequential API calls, assessing the API's performance in handling data conversions, logic branches, and conditional flows based on input data or external factors, ensuring data integrity and consistency, testing error handling and rollback procedures for workflow failures or exceptions, and confirming adherence to business rules, constraints, and regulatory requirements. Workflow testing is essential in validating the API's support for complex business processes and its ability to navigate real-world scenarios involving multiple API interactions and data conversions.

API Automation Testing

Automated testing is a great way to speed up the testing process, especially for regression testing and load testing. You can create automated tests that run every time you make changes to your API, ensuring that you catch any issues early on. They can be built into your CI/CD pipelines or run locally to make sure new changes don’t have unintended consequences.

Functional Testing Automation

Automating functional tests for APIs is a critical and common practice. This involves automating both positive and negative test scenarios, boundary value testing, equivalence partitioning, and data validation testing. Automated functional tests are crucial in verifying that the API functions as intended and handles different input scenarios effectively, including edge cases and errors.

Performance Testing Automation

Automating performance testing for APIs is vital for evaluating their performance under varying load conditions and pinpointing potential bottlenecks or scalability concerns. This encompasses automating load testing, stress testing, soak testing, and scalability testing. Automated performance tests can replicate simultaneous users, gauge response times, throughput, and resource usage, aiding in determining the API's maximum capacity.

Security Testing Automation

Automating security testing for APIs aids in recognizing and addressing potential security weaknesses. This includes automating tests for authentication and authorization vulnerabilities, injection attacks (SQL, XSS, XXE), data exposure, and encryption implementation flaws. Automated security tests can mimic different attack vectors and confirm that the API adheres to secure coding best practices and data security measures.

Contract Testing Automation

Contract testing, also referred to as Consumer-Driven Contract Testing (CDC), entails the automation of tests based on predetermined contracts or agreements between the API provider and consumers. Automated contract tests guarantee that the API complies with the specified behavior, data formats, and response structures outlined in the contract, thereby reducing integration challenges and fostering enhanced teamwork.

Regression Testing Automation

Automating regression tests for APIs is essential when implementing modifications or upgrades to the API. Automated regression tests aid in verifying that the existing functionalities operate as intended and that no new issues have emerged. This encompasses automating tests for different endpoints, input scenarios, and integration points.

Monitoring and Continuous Testing Automation

The automation of monitoring and continuous testing for APIs involves establishing automated tests that are periodically or continuously executed against the API within a staging or production environment. This proactive approach assists in identifying and resolving issues promptly, guaranteeing that the API sustains its anticipated behavior and performance consistently.

E2E Testing Automation

Automating end-to-end tests for APIs requires replicating entire workflows and scenarios across various API endpoints, integrations, and dependencies. Automated end-to-end tests are valuable for verifying the API's functionality in practical situations and confirming its seamless integration with different components and systems.

Data-Driven Testing Automation

Data-driven testing entails automating API tests that leverage external data sources or predefined test data sets. This method facilitates effective testing using diverse input data combinations and scenarios, thereby minimizing the manual effort needed to sustain and revise test cases.

Automated API Testing Tools

I’ve already mentioned the importance of adopting automation into your API process. There are many tools on the market for API testing including Insomnia, SoapUI, Postman, Grafana’s K6 and Selenium. These tools allow you to test your API endpoints, automate your testing process, and generate reports to help you analyze your results.

API Testing Webinar

Insomnia API Testing Solutions

Insomnia and Kong offer robust automated API testing solutions that cater to different needs and workflows.

Kong, with its innovative API management solutions, provides robust platforms like Kong Insomnia to cater to the multifaceted needs of API testing. Kong Insomnia stands out as a collaborative, open-source API development platform that simplifies and accelerates the process of building high-quality APIs. It offers a dev-friendly UI, reducing the complexity traditionally associated with API development. Users benefit from features like built-in automation for manual tasks and an extensible plugin ecosystem, which together, enhance developer productivity and efficiency. Unlike other tools that might be bloated and costly, Insomnia is designed to be lightweight and cost-effective, providing most of the functionality offered by competitors like Postman but at a fraction of the cost. With options for local, cloud, or Git storage, it facilitates better collaborative API building in teams. Insomnia's approach to API testing is geared towards not just meeting the current needs of developers but also reducing costs and tech debt, making it a holistic solution for organizations looking to lean into digital transformation with speed and security.

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