Why Should Testers Automate User Interface (UI) and Visual Regression Testing?

Seamless user experience is not just a perk, it’s a competitive edge.

Rigorous UI and visual regression testing help businesses ensure that their websites and mobile apps are user-friendly and thus, have that edge.

However, with the constant updates and changes in website and app features, handling these manually has become quite challenging. Therefore, organizations prioritize automating UI and visual regression testing to simplify the process.

This replaces manual efforts with automated scripts, speeds up workflows, and improves the efficiency of your QA processes.

This blog post will help you learn in detail how automating UI and visual regression testing can help you strike the right balance between thorough testing and streamlined efficiency. You will also learn which tools can help you efficiently achieve this.

Let’s begin!

Why Should You Automate UI Testing?

Faster Feedback Loop

Automation provides quick feedback on UI changes, enabling rapid identification and resolution of issues. This speeds up the development cycle and ensures quicker adjustments.

Increased Speed and Efficiency

Automation accelerates testing processes, executing repetitive tasks swiftly and consistently. This, therefore, expedites the testing phase and enables faster releases without compromising quality.

Enhanced Test Coverage

It allows for simultaneous testing across various devices, screen sizes, and platforms. The comprehensive test coverage helps you ensure potential issues are identified across diverse environments.

Improved Consistency and Standardization

Automated tests maintain uniform testing standards. This reduces inconsistencies seen in manual testing and ensures a high level of reliability across different testing cycles.

Lesser Human Errors

Leveraging UI automation helps you take control of test creation and execution, improve the reliability of your test project, and reduce human discrepancies.

What Are the Different Types of Automation Frameworks Used for UI Testing?

Selenium:

Selenium, an open-source automation testing tool, supports multiple scripting languages like Java, Perl, C#, Ruby, JavaScript, and others. This flexibility enables testers to choose the scripting language best suited for the application to be tested. Selenium also uses test scripts to perform various user actions on the web application’s interface and automate interactions with web browsers. It can execute the same tests across different browsers and versions, which makes Selenium an ideal tool for UI testing and cross-browser testing.

Cypress:

Cypress is a popular open-source test automation tool that offers the Cypress Dashboard as a professional service in its priced package. It supports various testing types like Unit, Integration, Component, API, and End-to-End Testing. It also records test videos and allows the configuration of screenshot options for your tests.

WebdriverIO:

The WebdriverIO framework has a longstanding presence. Functioning somewhat similar to Selenium with JavaScript, WebdriverIO internally employs Selenium libraries. Being open-source and affiliated with the OpenJS Foundation, WebdriverIO utilizes the Webdriver implementation, thus extending support to all major browsers. With almost 17 reporter types, it accommodates various reporting methods. Moreover, there are no constraints on parallel testing.

What Are the Best Practices to Leverage Cloud-Based Automation Solutions & Maintain a UI Test?

Utilizing automation tools and resources hosted on cloud platforms enables users to perform automated tasks using cloud-based infrastructure and services.

Businesses can leverage these cloud-based tools to access scalable computing resources, reduce infrastructure costs, and increase flexibility and accessibility. AWS Lambda, Azure Automation, Selenium Grid on Cloud, and Google Cloud Automation are some of the cloud-based automation solutions used across different domains.

To master the art of maintaining these UI tests, here are some best practices you can follow –

1. Set up a simple and user-friendly system for test maintenance that encourages smooth communication among team members.

2. Utilize a standardized template for all automated test cases to ensure consistency and efficiency across the board.

3. Develop reusable tests or leverage a tool that facilitates test reusability for enhanced efficiency and scalability.

4. Aim for maximum coverage upfront, when writing test cases and scripts. Doing so will reduce the need to constantly add new data for small code changes later on.

Why Should You Conduct Visual Regression Testing Using Automation Tools?

Visual Regression Testing operates similarly to UI testing, focusing solely on the visual components within the software.

These tests aim to uncover visual inconsistencies such as unaligned buttons, overlapped images or text, partially displayed elements, and irresponsive layout and rendering.

Automating regression tests eliminates the need for a dedicated QA team to run continuous test iterations. It also brings stable test results because all the system components tested are conducted with the same level of expertise.

Automated regression testing can be conducted 24/7 to ensure that regular updates are perfectly aligned and the need to allocate testing tasks to the QA team is terminated. This ultimately benefits the total test coverage since QA engineers can thoroughly run more tests and provide efficient assessment results.

Which Automation Tools Should You Use for Visual Regression Testing?

testRigor

testRigor analyzes various parameters and selects the most valuable ones, which helps ensure highly reliable tests. This tool enables the creation of tests using simple, human-readable language, referencing elements from a human perspective. Also, it significantly reduces test maintenance and takes an average of 95% less time.

Aye Spy

This tool, inspired by BackstopJS and Wraith, called Aye Spy, is an open-source visual regression tool that prioritizes performance. It relies on Selenium Grid for parallel testing across multiple computers, which is ideal for efficient cross-browser testing. Using Docker images of Selenium ensures consistent results. Its robust setup allows the comparison of up to 40 images in under a minute, which enhances testing performance.

Hermione.js

Hermione, an open-source tool, simplifies integration and visual regression testing. It’s advantageous to have prior familiarity with Mocha and WebdriverIO to get started with Hermione. The tool supports parallel testing across various browsers and efficiently manages computation issues using subprocesses. It enables the segregation of tests within a test suite by specifying a path to the test folder. Hermione is user-friendly, enabling developers to easily adapt custom commands and plugins as hooks, facilitating the design of versatile test ecosystems.

How to Choose the Right Automation Testing Frameworks?

Identify Project Requirements

Understand your project’s specific needs and intricacies. Define the functionalities, scope, and testing goals to align with an automation framework that best suits your project’s demands and complexities.

Set Automation Budget

Establish a realistic budget for automation testing. Consider the costs associated with tool licensing, infrastructure, and personnel. A well-defined budget ensures a judicious investment in incorporating automation tools and technologies without straining financially.

Evaluate Tech Stack Compatibility

Assess the compatibility of automation frameworks with your project’s technology stack. Ensure seamless integration with existing tools and technologies. A compatible tech stack promotes efficiency, reduces integration challenges, and enhances overall automation effectiveness.

Thorough Comparison of Frameworks

Systematically compare potential automation frameworks based on predefined prerequisites. Evaluate factors such as scripting language, reporting capabilities, test scalability, and community support. A comprehensive analysis aids in identifying the framework that aligns with your project’s unique requirements.

Validation of Selection

Validate the chosen automation framework through pilot projects or proof-of-concept implementations. This step ensures practical applicability, identifies potential challenges, and verifies the framework’s capability to meet your project’s testing objectives. Validation also minimizes risks and boosts confidence in your automation framework selection.

Where Does Automation Testing Fit in the CI/CD Pipeline?

Integrating automation into CI/CD pipelines thrives on the principle of “build fast, test fast, fail fast.”

The motive behind the CI/CD pipeline is implementing meaningful automation practices. Faster test failures and identification, constant feedback to the developers, and quick resolution make CI/CD test automation successful.

Automation testing in CI/CD removes redundant tasks and associated manual efforts. Higher test coverage, improved accuracy, and product consistency can also be ensured while doing so.

Incorporating UI testing into these pipelines ensures that every code change undergoes thorough UI validation and guarantees a smooth and error-free user experience.

It includes setting up automated tests that run whenever new code is integrated and deploying changes automatically after passing these tests.

Once the build phase is complete and unit tests are conducted, QA combines and verifies all the different builds, and finally executes integration tests.

Regression testing is the last verification stage after the application’s functionality and UI are tested.

Thus, automating testing stages, from units to regression, ensures thorough validation pre-deployment, boosting software efficiency and reliability in development and deployment.

The Bottom Line – The Future of Automation in UI & Visual Regression Testing

The future of UI testing automation is tied to AI-infused visual testing and defect detection. AI-based visual inspection elevates traditional visual inspection and leverages advanced algorithms, machine learning, and deep learning techniques to scrutinize images or videos for defects.

As compared to manual inspections, AI-based visual inspection enables improved precision, consistency, and efficiency. It handles vast data volumes swiftly and conducts inspections at remarkable speeds.

Regarding defect detection, AI-powered visual inspection automates the identification of flaws in manufactured goods. It identifies cosmetic issues, misalignments, faulty welds, or assembly errors, thus, helping you ensure high-quality products make it to market shelves.

Besides, there are self-healing and maintaining automation frameworks that tackle the primary issue in test automation script upkeep: object changes.

The image above explains how an ‘object’ refers to an element, like a webpage button or text box, that the script or user interacts with to execute tasks.

Therefore, automation is playing a pivotal role in adapting testing strategies to address the complexities of these new-age technologies like AI, IoT, blockchain, or augmented reality.

It will thereby continue to ensure comprehensive testing coverage, and faster validation across these innovative domains in the future.

Want to Learn More About Automating UI and Visual Regression Testing? Talk to Us!