No-Code Testing vs. Scripted Testing: Practical Examples and Complex Scenarios

Introduction

In the realm of software testing, choosing the right approach can significantly impact the efficiency and effectiveness of your testing strategy. No-code testing tools offer a user-friendly, quick-to-deploy option, while scripted testing provides the flexibility and control needed for complex applications. This article explores practical examples of both approaches, compares their advantages and disadvantages, and delves into the limitations of no-code testing when dealing with complex scenarios.

No-Code Testing Example

Scenario

A small e-commerce website wants to automate its smoke tests to ensure critical functionalities like login, product search, and checkout work correctly after every deployment. The team has limited technical skills.

Tool

Testim or TestProject (both are popular no-code testing tools).

Process

Create Tests:

• The QA team uses the no-code tool’s visual interface to record actions like navigating to the login page, entering credentials, searching for a product, adding it to the cart, and proceeding to checkout.
• Assertions are added visually, such as checking for the presence of the user’s name after login or verifying that the cart contains the correct product.

Run Tests:

• Tests are run directly from the no-code tool’s dashboard. The tool provides detailed reports and highlights any failed steps.

Maintenance:

• If the website UI changes, the QA team can quickly update the tests using the drag-and-drop interface without writing any code.

Advantages

• Quick setup and execution of tests.
• Non-technical team members can create and maintain tests.
• Rapid feedback on critical functionalities.

Disadvantages

• Limited flexibility for complex scenarios.
• Potential vendor lock-in with the chosen tool.

Scripted Testing Example

Scenario

A large banking application requires comprehensive end-to-end testing, including complex scenarios like multi-step transactions, varying user roles, and integration with external systems.

Tool

Selenium WebDriver (a widely used scripted testing tool).

Process

Create Tests:

• The automation team writes test scripts in a programming language like Java, Python, or C#. For example, a login test script in Python using Selenium might look like this:

from selenium import webdriver
from selenium.webdriver.common.by import By
from selenium.webdriver.common.keys import Keys
import time

driver = webdriver.Chrome()
driver.get("https://example-banking-app.com/login")

username = driver.find_element(By.NAME, "username")
password = driver.find_element(By.NAME, "password")
login_button = driver.find_element(By.ID, "login-button")

username.send_keys("test_user")
password.send_keys("secure_password")
login_button.click()

time.sleep(3)
assert "Welcome" in driver.page_source

driver.quit()

Run Tests:

• Tests are executed using a CI/CD pipeline like Jenkins. Each test run generates detailed logs and reports that can be analyzed by the team.

Maintenance:

• Scripts are maintained in a version control system (e.g., Git). Changes in the application require updates to the test scripts, which are done by the automation engineers.

Advantages

• High flexibility to handle complex test scenarios.
• Deep integration with development practices and tools.
• Scalable and customizable test execution.

Disadvantages

• Requires programming skills to create and maintain tests.
• More time-consuming to set up and update tests.

Comparison

• Ease of Use: No-code tools are easier to use and require less technical knowledge, suitable for smaller teams or projects with less complexity.
• Flexibility: Scripted tests offer more flexibility and can handle complex scenarios, making them ideal for larger, more intricate applications.
• Maintenance: No-code tests are easier to maintain initially, but as the application grows, they can become harder to manage. Scripted tests, while more complex to maintain, provide better long-term scalability and control.

Limited Flexibility for Complex Scenarios: What Can Be Complex Scenarios

No-code testing tools, while user-friendly and quick to set up, often struggle with complex scenarios due to their limited customization capabilities. Below are examples of complex scenarios that highlight the limitations of no-code testing tools:

1. Dynamic Data Handling

Scenario: An application that requires testing with dynamic data inputs that change based on previous actions or external data sources.

Complexity: No-code tools may struggle to fetch, manipulate, and use dynamic data from APIs, databases, or external files efficiently.

Example: A flight booking system where the test needs to select a flight based on real-time availability, then calculate prices including various taxes and fees, and finally verify the booking process. Handling such dynamic data requires custom scripting to fetch and process real-time data, which is often beyond the capabilities of no-code tools.

2. Conditional Logic and Loops

Scenario: Testing scenarios that require extensive use of conditional logic and looping.

Complexity: While some no-code tools support basic conditions, they often lack the depth needed for intricate test logic.

Example: An e-commerce application where the test must iterate through multiple user roles, each with different permissions and access levels, and verify access control and data visibility for each role. This requires looping through user roles and applying different test steps based on conditions, which is more naturally handled through scripting.

3. Cross-Browser and Cross-Device Testing

Scenario: Ensuring an application works consistently across different browsers and devices.

Complexity: No-code tools may not support extensive cross-browser/device testing, especially when dealing with unique behaviors and compatibility issues in various environments.

Example: A responsive web application that needs to be tested on multiple browsers (Chrome, Firefox, Safari, Edge) and devices (desktops, tablets, smartphones). Each combination might present unique issues such as layout differences or browser-specific bugs. Writing scripts allows for detailed and specific test adjustments per browser/device combination, something no-code tools might not handle well.

4. Integration with Complex Workflows

Scenario: Applications that interact with multiple external systems or services.

Complexity: No-code tools often have limited support for complex integrations and might struggle to coordinate actions across multiple systems.

Example: An enterprise resource planning (ERP) system that integrates with multiple services like payment gateways, inventory management systems, and shipping services. Testing such integrations requires handling complex workflows, API calls, and data synchronization, which typically necessitates custom scripts to manage the interactions and validate the entire workflow.

5. Performance and Load Testing

Scenario: Simulating a high number of users or transactions to test the application’s performance under load.

Complexity: No-code tools usually focus on functional testing and may lack robust features for performance and load testing.

Example: A financial application that needs to handle thousands of concurrent transactions. Testing the system’s performance under such load conditions requires simulating multiple concurrent users, managing session states, and monitoring system performance metrics, which is more effectively handled by scripted load testing tools like JMeter or custom scripts.

6. Advanced Data Validation and Verification

Scenario: Validating complex data transformations, calculations, and reports.

Complexity: No-code tools might not support advanced data verification techniques needed for thorough validation.

Example: A business intelligence application that generates complex reports from multiple data sources. Validating these reports involves checking numerous data points, ensuring data integrity, and verifying calculations. This often requires sophisticated data handling and validation logic that is easier to implement and maintain through scripting.

Conclusion

No-code testing tools excel in simplicity and ease of use, making them ideal for straightforward, repetitive tests. However, their limited flexibility makes them less suitable for complex scenarios that involve dynamic data, intricate logic, extensive integrations, performance testing, and advanced data validation. Scripted testing, on the other hand, provides the necessary control and customization to handle these complex scenarios effectively.

For a small e-commerce site, no-code testing provides a quick and easy way to ensure basic functionalities work correctly. For a complex banking application, scripted testing with Selenium offers the necessary flexibility and control to manage comprehensive end-to-end testing scenarios. A hybrid approach could also be considered, where no-code tools are used for simpler, repetitive tests, and scripted tests are used for more complex scenarios.