Are you grappling with the complexities of ensuring your APIs are robust, efficient, and secure while keeping up with rapid development cycles? Manual testing might leave gaps, introduce errors, and delay the discovery of critical defects. These challenges can hinder your development process, escalate costs, and ultimately affect the quality and reliability of your applications.
Adopting REST API automation testing can address these pain points effectively. By utilizing automated testing tools like Rest Assured and Postman, you can streamline your testing processes, achieve comprehensive coverage, and seamlessly integrate testing into your continuous integration and deployment pipelines.
What is API?
An Application Programming Interface (API) is a comprehensive set of protocols, routines, definitions, and tools that specify how software components should interact with each other. APIs serve as an essential intermediary that enables different software applications or systems to communicate and share data and services without needing to understand each other's underlying implementation details.
What is REST API?
A REST API (Representational State Transfer Application Programming Interface) is a web service interface that adheres to the principles of REST architecture, enabling communication between clients and servers over the internet using standard HTTP methods like GET, POST, PUT, and DELETE. It allows different software applications to interact by accessing and manipulating web resources identified by URLs, typically exchanging data in formats like JSON or XML in a stateless and uniform manner.
What is REST API automation testing?
REST API automation testing is the process of using specialized tools and scripts to automatically test RESTful web services. This practice ensures that APIs function correctly, meet specified requirements, and perform reliably under various conditions. By automating API tests, developers and testers can accelerate the testing process, increase coverage, reduce human error, and facilitate continuous integration and delivery in agile environments.
Now that we've defined REST API automation testing, it's crucial to recognize why this practice holds significant value in software development.
The Importance of REST API Automation Testing
REST API automation testing is a crucial component in modern software development, providing numerous benefits that enhance the quality and efficiency of applications. Here are the key reasons highlighting its importance:
Ensures Quality and Reliability: Automation testing thoroughly verifies that all API endpoints function as intended. It helps identify issues in the logic, data handling, and response formats, ensuring that the API meets the specified requirements and provides reliable service to consumers.
Accelerates Development and Deployment: Automated tests run faster than manual tests, offering immediate feedback to developers. This acceleration supports rapid development cycles and enables continuous integration and continuous deployment (CI/CD), allowing teams to release updates and new features more quickly.
Enhances Test Coverage and Efficiency: Automation allows testers to execute a vast number of test cases, including various input combinations and edge cases, which might be impractical manually. This extensive coverage ensures that more potential defects are identified and addressed.
Reduces Costs Over Time: While setting up automated tests requires an initial investment, they save significant time and resources in the long run by reducing repetitive manual testing efforts. This cost efficiency allows teams to allocate resources to other critical tasks.
Facilitates Early Detection of Defects: Integrating automated tests into the development pipeline enables the early detection of bugs and issues. Catching defects early in the development process prevents them from escalating into more significant problems later, saving time and reducing remediation costs.
Supports Agile and DevOps Practices: Automation is essential for Agile and DevOps methodologies, emphasizing iterative development and frequent releases. Automated testing ensures that code changes do not break existing functionality, supporting the continuous delivery model.
Provides Consistent and Repeatable Testing: Automated tests eliminate human error inherent in manual testing, ensuring that tests are executed consistently every time. This repeatability is crucial for reliable results and tracking code changes' impact over time.
With the importance established, let's explore the core concepts that form the foundation of effective REST API automation testing.
Core Concepts in REST API Automation Testing
1. In-depth understanding of HTTP Methods and Status Codes
A crucial aspect of REST API automation testing is a thorough comprehension of HTTP methods and status codes. Each HTTP method—such as GET, POST, PUT, DELETE, and PATCH—serves a specific purpose in interacting with resources:
GET: Retrieve data without affecting the server state.
POST: Create new resources.
PUT: Update or replace existing resources.
DELETE: Remove resources.
PATCH: Apply partial modifications to resources.
Understanding idempotency (methods that produce the same result no matter how often they're executed) and safe methods (methods that don't modify resources) is essential for accurate testing. Additionally, familiarity with HTTP status codes (e.g., 200 OK, 201 Created, 400 Bad Request, 404 Not Found, 500 Internal Server Error) enables testers to validate responses precisely and handle exceptions effectively.
2. Comprehensive Assertions and Response Validation
Effective REST API automation testing goes beyond checking if an API endpoint is reachable; it involves validating the correctness and integrity of responses. This includes:
Response Body Validation: Check that the response body contains the expected data, structures, and types. JSON or XML schema validation ensures the response adheres to the specified contract.
Header Verification: Ensuring that response headers contain necessary metadata like Content-Type, Authorization, and Cache-Control, which can affect how clients process the response.
Data Integrity Checks: Verifying that the data returned matches the input criteria and business rules. This may involve complex assertions on nested data structures.
Error Handling Validation: Testing how the API responds to invalid inputs or unexpected conditions, and ensuring that appropriate error messages and status codes are returned.
By implementing detailed assertions, testers can catch subtle bugs and discrepancies that might be missed with superficial testing.
3. Automation of Authentication and Authorization Mechanisms
Many REST APIs require authentication and enforce authorization to protect resources. Automating these aspects involves:
Token Management: Handling API keys, OAuth tokens, or JWTs within automated tests. This includes obtaining tokens programmatically, refreshing them when they expire, and invalidating them when necessary.
Role-Based Access Testing: Verifying users with different roles or permissions have appropriate access levels. This ensures that restricted endpoints are not accessible without proper authorization.
Secure Credential Handling: Securely storing and managing sensitive information within the test framework. Utilizing environment variables or secure vault services prevents credential leakage.
Session Management: For APIs that maintain sessions, tests need to handle session creation, maintenance, and termination appropriately.
Automating authentication and authorization tests ensures that security controls are consistently enforced, reducing the risk of unauthorized access.
4. Implementation of Data-Driven Testing Strategies
Data-driven testing involves running test scenarios with multiple input data sets to cover a wide range of conditions and edge cases. In REST API automation testing, this approach enhances test coverage and efficiency:
External Data Sources: Utilizing CSV files, Excel spreadsheets, JSON files, or databases to feed input data into test scripts. This allows for easy maintenance and scalability of test data.
Parameterization: Designing tests that accept input parameters like query parameters, request bodies, and headers. This makes tests reusable and adaptable to different scenarios.
Edge Case Testing: Including boundary values, nulls, and invalid data formats to test the API's robustness and error handling capabilities.
Automated Data Generation: Using tools or scripts to generate large volumes of test data dynamically, which is especially useful for performance and load testing.
Data-driven testing helps identify defects that may not be apparent when using static or hard-coded values.
5. Integration with Continuous Integration/Continuous Deployment (CI/CD) Pipelines
Incorporating REST API tests into CI/CD pipelines ensures that testing is an integral part of the development process, leading to faster feedback and higher-quality software:
Automated Test Execution: Configuring CI/CD tools like Jenkins, Travis CI, or GitLab CI/CD to run tests automatically upon code commits, pull requests, or scheduled intervals.
Environment Management: Setting up different environments (development, staging, production) and ensuring tests run against the appropriate environment with correct configurations.
Reporting and Notifications: Generating detailed reports on test outcomes and integrating notification systems (e.g., email, Slack) to alert teams of failures immediately.
Artifact Management: Storing and managing test results, logs, and related artifacts for auditing and historical analysis.
Scalability and Parallel Execution: Running tests in parallel to reduce execution time, which is crucial for large test suites.
Integrating tests into CI/CD pipelines promotes a culture of continuous testing and allows teams to detect and address issues early in the development cycle.
Understanding these core concepts prepares us to implement practical testing strategies. One such approach involves using specialized tools like Rest Assured.
REST API Testing with Rest Assured
Rest Assured is a powerful Java library designed to simplify the testing of RESTful web services. It provides a domain-specific language (DSL) that allows testers and developers to write readable, maintainable tests for API endpoints. By integrating Rest Assured into your testing framework, you can automate the validation of API responses, ensuring that your services function as expected.
Prerequisites
Before you begin, ensure you have the following:
Java Development Kit (JDK) installed on your system.
An Integrated Development Environment (IDE) like Eclipse or IntelliJ IDEA.
Maven for dependency management.
Basic understanding of Java programming and RESTful APIs.
Interpreting HTTP Status Codes
Understanding HTTP status codes is crucial in verifying API responses:
2xx Success Codes:
200 OK: The request was successful.
201 Created: A new resource was successfully created.
204 No Content: The request was successful, but there's no content to return.
4xx Client Error Codes:
400 Bad Request: The request was invalid or cannot be served.
401 Unauthorized: Authentication is required.
404 Not Found: The requested resource could not be found.
5xx Server Error Codes:
500 Internal Server Error: A generic error occurred on the server.
503 Service Unavailable: The server cannot handle the request at the moment.
Setting Up Rest Assured
1. Create a New Maven Project
Open your IDE and start a new Maven project.
Define the Group Id (e.g., com.example) and Artifact Id (e.g., rest-assured-testing).
2. Add Rest Assured Dependency
In your project's pom.xml file, add the Rest Assured dependency to manage the library:xml<dependencies>
<dependency>
<groupId>io.rest-assured</groupId>
<artifactId>rest-assured</artifactId>
<version>5.3.0</version>
<scope>test</scope>
</dependency>
</dependencies>
Save the file and allow Maven to download the necessary dependencies.
Writing Test Cases with Rest Assured
Rest Assured supports testing of various HTTP methods used in RESTful APIs. Below are the steps to test common HTTP methods: GET, POST, PUT, PATCH, and DELETE.
1. Testing a GET Request
Objective: Retrieve information from a specific URL and verify the response.
Steps:
Set Base URI: Define the base URL of the API you are testing.
Specify Request Details: Prepare any necessary query parameters or headers.
Send the Request: Use Rest Assured to send a GET request to the desired endpoint.
Validate the Response: Check the status code and verify that the response body contains the expected data.
Example Scenario:
Endpoint: https://reqres.in/api/users?page=2
Expected Status Code: 200 OK
Validation: Ensure that the response contains a list of users for page 2.
2. Testing a POST Request
Objective: Create a new resource on the server and verify its creation.
Steps:
Prepare Request Body: Create a JSON object containing the data for the new resource.
Set Headers: Specify the Content-Type as application/json.
Send the Request: Use Rest Assured to send a POST request with the request body.
Validate the Response: Check for a 201 Created status code and verify that the response body reflects the newly created resource.
Example Scenario:
Endpoint: https://reqres.in/api/users
Expected Status Code: 201 Created
Validation: Confirm that the response includes the name and job title sent in the request.
3. Testing a PUT Request
Objective: Update an existing resource or create it if it doesn't exist.
Steps:
Prepare Request Body: Define the updated data for the resource.
Set Headers: Ensure the Content-Type is application/json.
Send the Request: Use a PUT request to update the resource at the specified URL.
Validate the Response: Expect a 200 OK status code and verify the response reflects the updates.
Example Scenario:
Endpoint: https://reqres.in/api/users/2
Expected Status Code: 200 OK
Validation: Check that the user's information has been updated accordingly.
4. Testing a PATCH Request
Objective: Partially update a resource with new information.
Steps:
Prepare Partial Data: Include only the fields that need to be updated.
Set Headers: Use application/json for the content type.
Send the Request: Issue a PATCH request to the resource's URL.
Validate the Response: Look for a 200 OK status code and confirm that only specified fields have changed.
Example Scenario:
Endpoint: https://reqres.in/api/users/2
Expected Status Code: 200 OK
Validation: Verify that the specific fields provided in the request body are updated.
5. Testing a DELETE Request
Objective: Remove a resource from the server.
Steps:
Set Headers (if necessary): Sometimes, you might need to include authentication tokens.
Send the Request: Use a DELETE method targeting the resource's URL.
Validate the Response: Typically, expect a 204 No Content status code indicating successful deletion.
Example Scenario:
Endpoint: https://reqres.in/api/users/2
Expected Status Code: 204 No Content
Validation: Confirm that the resource no longer exists by attempting a GET request and expecting a 404 Not Found.
Best Practices for REST API Testing with Rest Assured
Use Assertions Wisely: Always validate both the status code and key elements of the response body to ensure comprehensive testing.
Parameterize Tests: Utilize variables for endpoints and parameters to make tests reusable and maintainable.
Handle Response Data: Extract data from responses when needed, especially for chaining requests.
Implement Error Handling: Test how the API handles invalid inputs or unexpected conditions.
Organize Test Cases: Group related tests into classes or packages for better organization.
Now let's explore the steps to perform REST API automation testing using Postman.
REST API Automation Testing with Postman: Step-by-Step Guide
Postman is a widely-used API client that simplifies the process of creating, testing, and documenting APIs. It provides a user-friendly interface to send HTTP requests and inspect responses, making it an excellent tool for automating REST API testing. Let's walk you through the steps to perform REST API automation testing using Postman.
Prerequisites
Postman Installed: Download and install Postman from the official website.
Basic Understanding of REST APIs: Familiarity with HTTP methods (GET, POST, PUT, PATCH, DELETE) and status codes.
An API to Test
Steps to Automate REST API Testing with Postman
1. Launch Postman and Create a New Collection
Open Postman: Launch the Postman application on your computer.
Create a Collection: Click on the "Collections" tab and then the "+" icon to create a new collection. Name it something meaningful, like "REST API Automation Tests".
Purpose: Collections help you organize your API requests and tests in one place.
2. Add a New Request to the Collection
Create Request: Within your new collection, click "Add Request".
Name the Request: Provide a name, such as "Get Users", for easier identification.
Select HTTP Method: Choose GET from the dropdown menu next to the request name.
3. Testing a GET Request
Step-by-Step
Enter the Request URL:
Paste the following URL into the request field: https://reqres.in/api/users?page=2.
Set Parameters or Headers (if necessary):
For this basic GET request, no additional parameters or headers are required.
Send the Request:
Click the "Send" button to execute the request.
Verify the Response:
Status Code: Ensure the status code is 200 OK, indicating a successful request.
Response Body: Check that the response body contains the expected data, such as a list of users.
Interpretation
A 200 OK status means the GET request was successful, and the data was retrieved as expected.
4. Testing a POST Request
Step-by-Step
Add a New Request:
Name it "Create User" and select the POST method.
Enter the Request URL:
Set Headers:
Click on the "Headers" tab.
Add a new header with Key: Content-Type and Value: application/json.
Prepare the Request Body:
Click on the "Body" tab.
Select "raw" and choose "JSON" from the dropdown.
Enter the JSON data:json{
"name": "John Doe",
"job": "Software Engineer"
}
Send the Request:
Click "Send".
Verify the Response:
Status Code: Should be 201 Created, indicating a new resource was successfully created.
Response Body: Contains the created user's details, including an id and createdAt timestamp.
Interpretation
A 201 Created status confirms that the POST request successfully added a new user to the system.
5. Testing a PUT Request
Step-by-Step
Add a New Request:
Name it "Update User" and select the PUT method.
Enter the Request URL:
Use https://reqres.in/api/users/2 (assuming we're updating user with ID 2).
Set Headers:
Key: Content-Type, Value: application/json.
Prepare the Request Body:
In the "Body" tab, input:json{
"name": "Jane Smith",
"job": "Project Manager"
}
Send the Request:
Click "Send".
Verify the Response:
Status Code: Should be 200 OK.
Response Body: Contains the updated user information and an updatedAt timestamp.
Interpretation
A 200 OK status indicates the user's information was successfully updated.
6. Testing a PATCH Request
Step-by-Step
Add a New Request:
Name it "Modify User Job Title" and select the PATCH method.
Enter the Request URL:
Set Headers:
Key: Content-Type, Value: application/json.
Prepare the Request Body:
Input the partial data to update:json{
"job": "Senior Developer"
}
Send the Request:
Click "Send".
Verify the Response:
Status Code: Should be 200 OK.
Response Body: Shows the updated job field and an updatedAt timestamp.
Interpretation
The PATCH method successfully updated the specified field of the user resource.
7. Testing a DELETE Request
Step-by-Step
Add a New Request:
Name it "Delete User" and select the DELETE method.
Enter the Request URL:
Send the Request:
Click "Send".
Verify the Response:
Status Code: Should be 204 No Content.
Response Body: Typically empty, as the resource has been deleted.
Interpretation
A 204 No Content status confirms the user was successfully deleted from the system.
8. Adding Tests for Automation
To automate validation, you can add test scripts that assert expected outcomes.
Step-by-Step
Navigate to the "Tests" Tab:
In any request, click on the "Tests" tab below the request URL field.
Write Test Scripts:
Use Postman's built-in JavaScript library to write assertions.
Example:javascriptpm.test("Status code is 200", function () {
pm.response.to.have.status(200);
});
Common Assertions:
Status Code Verification:javascriptpm.test("Status code is 201", function () {
pm.response.to.have.status(201);
});
Response Time Check:javascriptpm.test("Response time is less than 500ms", function () {
pm.expect(pm.response.responseTime).to.be.below(500);
});
Content Verification:javascriptpm.test("Response contains user name", function () {
pm.expect(pm.response.json().name).to.eql("John Doe");
});
Save the Tests:
After adding your scripts, click "Save" to store them in the request.
Benefit
Automating tests ensures that each time the request is run, Postman will automatically verify the response against your assertions.
9. Running Tests Using the Collection Runner
Step-by-Step
Access the Collection Runner:
Click on the "Runner" button (usually at the bottom left of Postman).
Configure the Run:
Select your collection ("REST API Automation Tests").
Choose the environment if you have one set up.
Configure iterations if you want to run the tests multiple times.
Start the Run:
Click "Start Run".
View Results:
After the run completes, you'll see a summary of passed and failed tests.
Expand individual requests to see detailed results.
Benefit
The Collection Runner allows you to execute all your tests in sequence, providing a comprehensive overview of your API's functionality.
10. Data-Driven Testing with External Files
For advanced automation, you can run tests with data from external files (JSON or CSV).
Step-by-Step
Prepare Data File:
Create a JSON or CSV file containing your test data.
Example (data.json):json[
{ "name": "User1", "job": "Developer" },
{ "name": "User2", "job": "Tester" }
]
Load Data File in Runner:
In the Collection Runner, click "Select File" next to "Data" and choose your data file.
Access Data in Tests:
Use variables in your requests to utilize data from the file.
Example:
In the request body:json{
"name": "{{name}}",
"job": "{{job}}"
}
Run the Collection:
Execute the run, and Postman will iterate over each data entry.
Benefit
Data-driven testing allows you to test multiple scenarios efficiently, improving test coverage.
11. Using Newman for CLI Automation
Newman is Postman's command-line tool that enables you to run collections from the terminal, which is useful for integrating into CI/CD pipelines.
Step-by-Step
Install Newman:
Ensure you have Node.js installed.
Run npm install -g newman in your terminal.
Export Your Collection:
In Postman, click on your collection's options and select "Export".
Save the collection as a JSON file.
Run the Collection with Newman:
Execute the following command:bashnewman run your_collection.json
Include additional options as needed (e.g., environment files, reporters).
Review Results:
Newman will display the test run results in the terminal.
Benefit
Using Newman allows you to automate tests in various environments and integrate them with continuous integration systems.
Best Practices
Organize Requests: Group related API requests into folders within your collection.
Use Environments: Create environments for different stages (development, staging, production) and switch between them easily.
Secure Sensitive Data: Use environment variables to store API keys or tokens, and avoid hardcoding them.
Version Control: Use Postman's integration with version control systems to manage changes.
Regularly Update Tests: Keep your tests up to date with API changes to maintain reliability.
Automating REST API testing with Postman streamlines the validation process, ensures consistent test execution, and helps catch issues early in the development cycle. By following the steps outlined, you can set up comprehensive tests for all HTTP methods, utilize data-driven testing, and integrate your tests into automated pipelines using Newman.
Let's understand why load testing is a critical component of API performance optimization.
Maximizing REST API Performance: Load Testing Essentials
The performance of RESTful APIs is critical to the success of web and mobile applications.
As user expectations rise for instantaneous responses and seamless experiences, any lag or downtime can lead to user dissatisfaction and revenue loss.
Load testing is a crucial practice for ensuring that your REST APIs can handle the expected load while maintaining optimal performance. Let’s delve into the essentials of load testing REST APIs, offering valuable insights to help you maximize their performance effectively.
Understanding the Importance of Load Testing
Load testing involves simulating real-world usage by generating high requests to your API and observing how it behaves under stress. It helps identify performance bottlenecks, scalability issues, and points of failure that may not be apparent during functional testing.
By proactively conducting load tests, you can ensure that your API maintains high performance and reliability even during peak usage, enhancing user satisfaction and trust.
Defining Clear Performance Objectives
Before initiating load testing, it's imperative to establish clear performance goals based on user expectations and business requirements. Determine key metrics such as maximum response times, throughput (requests per second), concurrency levels, and acceptable error rates.
For instance, you might set a target that 95% of API responses should be delivered within 200 milliseconds under a load of 1,000 concurrent users. These objectives provide a benchmark against which to measure your API's performance and identify improvement areas.
Simulating Realistic User Behavior
Effective load testing requires accurately mimicking how users interact with your API. This involves creating test scenarios that reflect real user behavior, including the various endpoints accessed, the frequency of requests, and the data payloads used. Incorporate different user paths and workflows to ensure comprehensive coverage.
Choosing the Right Load Testing Tools
Selecting an appropriate load-testing tool is crucial for executing your strategy efficiently. Tools like Apache JMeter, Gatling, k6, and Locust are popular REST API load testing choices. These tools allow you to script complex test scenarios, parameterize inputs, and collect detailed performance metrics.
Evaluate tools based on criteria such as ease of scripting, scalability, reporting capabilities, and integration with your existing development and monitoring systems.
Designing Comprehensive Test Scenarios
Develop test scripts covering various scenarios, from normal operational loads to peak traffic conditions. Start with baseline tests to understand how your API performs under minimal load. Gradually increase the load to progress to stress tests to identify your API's breaking point.
Conduct spike tests by introducing sudden increases in load to assess how your API handles abrupt traffic surges. Soak tests involving sustained load over an extended period can help uncover issues like memory leaks and resource depletion.
Implementing Parameterization and Dynamic Data Handling
To simulate a realistic load, your test scripts should use parameterization to vary input data and avoid caching effects that could distort results. Incorporate different user credentials, IDs, and data payloads.
Handle dynamic data such as session tokens and authentication keys by capturing and reusing them during the test run. This ensures that each virtual user operates independently, providing a more accurate simulation of real-world usage.
Monitoring and Analyzing Performance Metrics
During load testing, monitor critical performance indicators, including response times, throughput, error rates, CPU and memory usage, and network latency. Use these metrics to identify patterns and anomalies.
For example, increasing response times or error rates under higher loads may indicate server bottlenecks or database constraints. Analyze logs and utilize profiling tools to drill down into the causes of performance degradation.
Optimizing Based on Test Findings
The insights gained from load testing should guide your optimization efforts. Consider indexing, query optimization, or database scaling if you identify database bottlenecks.
Look into code optimization, efficient resource management, and implementing asynchronous processing where appropriate for server-side issues.
Implement caching strategies at various layers, such as in-memory caches for frequent read operations, to reduce load on backend systems. Load balancing and horizontal scaling can also distribute traffic more evenly across servers.
Iterative Testing and Continuous Improvement
Load testing should not be a one-time activity. Incorporate it into your development lifecycle, especially after significant code changes or infrastructure updates. Continuous load testing helps you catch performance regressions early.
Use automation to integrate load tests into your CI/CD pipelines, ensuring that every new release meets your performance standards. Regular testing allows you to adapt proactively to changing usage patterns and scale requirements.
Documenting Results and Sharing Insights
Maintain detailed records of your load testing processes, configurations, and results. Document any changes made to the system and their impact on performance. Share these insights with your development and operations teams to foster a culture of performance awareness. Collaborative analysis can lead to more effective solutions and innovations that enhance overall system performance.
Best Practices for Effective Load Testing
Start Small and Scale Gradually: Begin with a small load and incrementally increase it to monitor how performance metrics change. This approach helps isolate issues at different load levels.
Isolate the Test Environment: Use a dedicated environment that mirrors production to avoid affecting live users and to obtain accurate results.
Validate Test Accuracy: Validate responses and check for errors in the test itself to ensure that your test scripts are functioning correctly.
Monitor End-to-End Performance: Look beyond the API server to include database performance, network latency, and third-party service integrations.
Consider Geographic Distribution: If your users are globally distributed, simulate load from different regions to account for network variances.
Conclusion
Ensuring the robustness, efficiency, and security of your APIs is crucial in today's interconnected digital landscape. REST API automation testing stands out as an essential practice that not only improves the quality and reliability of your services but also accelerates development cycles and reduces costs. Embracing REST API automation testing is more than a technical enhancement—it's a strategic investment in your organization's success.
At ToolPioneers, we specialize in building custom software applications using Retool, focusing on seamless API integration to connect your apps with a wide array of data sources and services. Our expertise enables you to interact efficiently with various APIs, enhancing your application's functionality and performance without the complexities of managing underlying implementation details.
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