Best Practices For Visual Regression Testing On Cloud

19 August 2023

Visual regression testing is the software testing process that is used to test your software application by visually finding any error or malfunctioning in the user experience. Visual regression testing ensures that an application or website maintains its intended look and behavior. It confirms the absence of any unplanned alterations to its visual design or functionality.

This procedure entails comparing a reference version of the application or website and its current version, aiming to identify any visual disparities.

Visual regression testing in a Cloud-based platform is the latest trend in the field of software testing and automation testing. It has various advantages, such as it increases the testing scope, costs less, and it increases testing flexibility.

In this article, you will see the concepts of visual regression testing on the cloud, best practices for it, and many such things.

What is Visual Regression Testing

Visual regression testing evaluates the impact of code changes on the user experience by comparing screenshots before and after execution. It’s also recognized as visual snapshot tests or visual testing, and its primary objective is to uphold visual consistency following updates.

The Function Of The Visual Regression Testing

Visual testing validates the suitability of an application’s user interface in terms of its visual attributes. This quality assurance process aims to confirm the accurate display of content and data on the application’s front end.

In case you’re not acquainted with the concept of Regression testing, its purpose is to ensure that any modifications made to the software do not disrupt any previously functioning elements. In the context of visuals, this testing guarantees that alterations to the software do not lead to style-related problems.

The true capability of visual regression testing can be leveraged with Cloud-based AI-powered test orchestration and execution platforms like LambdaTest. It allows the running of visual testing across a large farm of 3000+ real device and OS combinations. This helps to ensure cross platforms compatibility on the visual appearance and interface of the software applications.

Features Offered By The Cloud-Based Ai-Powered Test Orchestration And Execution Platform – Lambdatest For Robust Visual Regression Testing Are As Follows:

This section discusses the features which are offered by the test orchestration and the execution platform.

Execute Selenium and Cypress tests across a range of programming languages, such as Java, NodeJS, C#, Python, and StoryBook. This empowers the delivery of flawlessly designed applications across almost any browser or device.
Employ Mis-match Ignore feature of SmartUI’s Status Bar so that you can tackle the complexities of visual differentiations. This capability allows testers to crop the status bar out from the screenshots. Leveraging the high-end technique of image processing, it accurately detects and eliminates the status bar. This facilitates the analysis of essential UI components with due focus.
Effortlessly install, set up, and execute the LambdaTest NPM package. This enables the direct implementation of the JS scriptsStorybook via our NPM CLI.
Conduct regression testing, the visual ones for your mobile apps on genuine devices. Assure visual uniformity with precise pixel-to-pixel comparisons against your reference point, encompassing various screen sizes, resolutions, and layouts.

Best Practices for Visual Regression Testing on Cloud

Let us see the practices a tester must follow while performing visual regression testing on a cloud-based platform like LambdaTest.

Following these practices during the test automation will make your software application visually more powerful and efficient.

1. Tool Selection:

Choosing the appropriate tool to perform visual regression testing on the LambdaTest is one of the most important and essential steps in moving ahead of the testing process. Various parameters should be kept in mind during the tool selection for testing automation, such as the software type, compatibility aspects, resolution, etc. LambdaTest integrates with various tools like Selenium, Cypress, Playwright, and others, using which you can perform visual regression testing.

2. Consistent Environment:

Never forget to create a conducive setup that will facilitate cloud-based visual regression testing. The interface provided by using these environments allows you to examine the visual outcomes and input received during the testing process. The testing team has the ability to pause the visual regression testing procedure and make the necessary corrections.

The team conducting the testing should also maintain resource isolation for the environment. It aids in preventing any type of intervention during automation testing, which increases the effectiveness and productivity of cloud-based visual regression testing.

3. Isolation And External Factors:

Remember that the isolated environment should not be affected by any external factors. They include network latency or fluctuations, system updates, or background processes running on the testing machine. These factors may lead to visual error and malfunctioning of the software application. External influences can potentially introduce visual errors and cause malfunctions in the software application.

Ensuring a controlled environment by addressing the factors safeguards the accuracy of the testing results. All the screenshots and visual reports of the testing process will be saved in that specific folder. This will help to perform visual comparisons effectively.

4. Scriptless Test Cases

Visual regression testing on the cloud platform using scriptless test cases is the best approach. Since numerous cloud-based AI tools are available, test automation can be utilized to develop test cases simultaneously. It is because the testing scope of a programmed test case is limited.

But using AI technologies offered by LambdaTest for test case design opens up possibilities for the testing team to consistently cover the testing scope. It will perform visual testing against some test cases, and again, it will recreate the test cases according to the previous result and analysis. This practice will bring the best visual result for your software application.

5. Documentation Of Visual Test Cases

Documentation is a very effective and important practice in any software testing process. In visual regression testing, you need to test and verify the components visually, and here it is important to mark down your observations, bugs, and analysis and work on them accordingly.

For your visual regression tests performed in LambdaTest, you should create clear and succinct test cases and descriptions. You should also include comments or annotations to describe the aim and scope of your baselines and screenshots.

Additionally, you should preserve and maintain your screenshots and baselines using a version control system or a cloud-based service. Sharing and communicating with the client will help you understand their demand and make the best possible result.

6. Updating The Baseline

Updating the baseline is a very crucial step in the visual regression testing process when performed in LambdaTest. It consists of the practice of taking the feedback result and analyzing them. If the result is considerable, you can approve this update in the baseline. And if you think that it is not worth consideration, you can simply reject them. But you need to mention all these in the baseline. It is because this will help you in the future because you can see all your testing logs in the baseline.

Mention the changes that were done intentionally, their reasons, and such things. It will also help all the team members have an overview of the changes that are going on in the software testing process.

6. Optimize Testing Coverage And Scope

Always remember to prioritize the testing scope for each component, specifically when executing visual regression testing in cloud platforms like LambdaTest. The high-priority components must be paid more attention, and they should be executed with high precision.

Use the concept of full-page and component-based screenshots to compare the changes visually by the testing team. Using this practice in visual regression testing will help achieve a better UI experience and enhance the testing results. You can use some advanced features like custom attributes.

These attributes help find the elements separately during visual regression testing. Also, you can use the trigger events and DOM concept. These will help to perform the screenshot comparison effectively.

7. Performing Parallel Testing

Apart from this, you can leverage parallel test execution in performing visual regression testing in LambdaTest. Executing parallel testing is what makes visual regression testing productive and effective, though, along with those other factors.

8. Learn From Failure

It is the final practice that all testers must follow to perform visual regression testing on the cloud and during test automation. Learn from your previous failure. Document the mistakes that you have made previously. Write down the tool feedback and in which specific tool you got some issues performing the testing process. And learn from these highlights.

Make your testing goal and work on your failures. This will bring the best result for your software application. Also, it will help in the overall development of the organization as well as the individual tester. You should follow These best practices while performing visual regression testing on the cloud.

Conclusion

Visual regression testing is mainly used to find any kind of visual malfunctioning and errors in the software. Visual inconsistency is one of the major reasons that lead to decreased number of users of a product.

Some of the best practices that every testing team should follow to perform visual regression testing using the cloud are the selection of appropriate tools, using documentation, using AI-based test cases, etc. Various tools can be used to automate testing and perform visual regression testing on the cloud, such as LambdaTest.

Hope you get an understanding of the best practices for visual regression testing using the cloud and their various aspects after reading this article.

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Arnab

Arnab is a professional blogger, having an enormous interest in writing blogs and other jones of calligraphies. In terms of his professional commitments, He carries out sharing sentient blogs.

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Basic Knowledge on Flow Meters

In ancient history, resources are abundant, but with the fast-growing population of the earliest civilization, it’s either compromise or face the wrath of bloody conquest. Flow meters are widely used equipment that can create miracles in the 21st Century. To avoid bloodshed, the earliest civilization were civilized enough to meet an agreement regarding everything, and this would include water resources. Flow meters can make things easier for you. It can help you to achieve your goals. The wisest engineers of their time created a way to distribute the water from a nearby river equitably. They aim to justifiably distribute enough water to each city with accordance to their population’s needs. Thus, given only the flow of the river and with the help of mathematics, they strategically developed a way to measure the amount of distribution of water in the aqueducts of each city. The answer to their problem is flow measurement or flow meter. Up to this day, this system and the works are still applicable to our modern day plumbing and has helped engineers throughout the globe in flow measurement challenges. Essential Factors To Know About Flow Meters There are several essential factors that you need to consider about the flow meters while you want to get the things done in the correct order. Flow Measurement Importance: Typically, in a household setting, this is very much needed to regulate gas or water flow through installation or fixing. In layman’s term, it helps your plumber troubleshoot with your clogged sink or toilet. But for mass production factories, engineers like chemical, mechanical and application engineers use this to understand what went wrong, how to maximize production, if the process is accurate. Flow measurement is essential to have a smooth-flowing operation of their products. What is Flow Meter? The most basic stuff you need to know about flow measurement is flow meter. Basically, this is an instrument that measures volumetric flow (Q) denoted in a unit of cubic meters per second, linear or nonlinear mass indicated by kilograms, pounds, etc.. A typical flow meter design would include parts like paddlewheel sensor, locknut, built-in temperature sensor, and pipe tee. Flow Meter Appropriation: There are all sorts of type of flow meters available in the market, but you can’t just buy one and try it on the operation. Unless you know what you are doing and you were told to buy so, other than that, you won’t have a problem. Though having a lot of options for this instrument is liberating, this is also a disadvantage for personnel. Personnel should know how a particular device works to avoid miscalculations. Staff should also be knowledgeable for recalibration if needed. Staff should also be prepared for casual maintenance. There’s a lot more to consider like fixing the instrument, etc. The flow meter should be chosen wisely to reduce expenses. Guidelines When Choosing a Flow Meter: What fluid do you intend to measure? How viscous is the liquid you intend to measure? Do you also want a rate measurement? Which do you prefer a primary local display on your instrument or electronic signal output? What are the limitations of your chosen instrument based on flow rate, temperature, and pressure? Will the liquid not dissolve your instrument? Common Types of Flow Meter: Ultrasonic Flow Meter: If you intend in using this instrument is waste waters or other dirty fluids; ultrasonic flow meter is more applicable in this kind of areas. The Doppler Effect or the frequency shift is necessary during operations to harness suspended particles and gas bubbles at large. Variable Area Flow Meter: Also called Rotameters, this flow meter is a low cost and a simple instrument efficient for liquid and gas flow measurement. It also displays a wide rangeability of flow measurement, low-pressure drop, and linear output. Vortex Meters: If you want an instrument that quickly detects sudden fluctuations in process conditions or turbine meters, this flow meter is what you are looking for. Vortex meter possesses a low sensitivity quality to variation in the operation. This type also is available in many sizes and doesn’t sting in the wallet; that is why many users prefer it. Spring and Piston Flow Meter: This type somewhat looks likes a rotameters because of the tapered tube, used in both instruments. It must be situated in the no-flow position through a calibrated spring. This is more preferred than rotameters because it is user-friendly and economically friendly. It can also transmit electrical signals, and the design is much simpler. Paddlewheel Sensors: It is the most popular flow meter for water and water-like substances, but it is essential to check the compatibility of the fluid to be measured and the sensor. The rotor of this instrument is situated perpendicularly to the flow; thus, a better opportunity for personnel to avoid contact in case of toxic fluid is measured. Turbine Flow Meter: This instrument gives an accurate reading for the flow measurement, providing only a 0.5 probability of error. The Turbine Flow meter looks like a paddlewheel sensor with the rotor perpendicularly situated to the flow and is hanged in the fluid stream. Due to its accuracy, it is highly recommendable if the liquid to be measured is made of clean and viscous liquid. Read Also: Four Basic Types Of Water Flow Meters Tools Used In Building Surveying Add Accuracy To Your Testing With The Help Of Multimeter

6 Tech Conferences You Don’t Want to Miss This Year

Technology has greatly transformed the way we do business. The benefits cut across all elements of productivity, from speed and efficiency to storage and connectivity. Networking and collaboration with like-minded cohorts play an important role in promoting the adoption of technology. The same can be achieved through Tech conferences, where attendees get the opportunity to raise their individual profiles and careers. According to the INC Magazine, technology conferences also offer a platform to learn, gather content, and share information. Learning is the greatest motivation for attending conferences. While at the conference, attendees can follow proceedings and share content through blogs, tweets, and live feeds. Every year, hundreds of technology conferences are held all across the world bringing together various stakeholders. According to My Business, here are 6 tech conferences and fairs you cannot afford to miss: 6 Tech Conferences 1. Consumer Electronics Show (CES) Las Vegas : January 9 – 12 This annual event is often seen as the showpiece and launchpad for cutting-edge technology and innovation expected to transform the world over the coming decades. The event is organized by the Consumer Technology Association (CTA) and brings together business leaders, thinkers, innovators, and tech enthusiasts from all over the world. Event Website: www.ces.tech 2. SXSW – Austin : March 9 - 17 This annual technology event takes place in Austin, Texas. The event offers professionals from various backgrounds an effective platform to learn and create business opportunities in technology, music and filming, and other industries. The 3-day disruptive event regularly attracts key speakers from large tech concerns like Google, IBM, and Facebook. Event Website: www.sxsw.com 3. CeBIT – Hanover : June – 11 - 15 The CeBIT event in Hanover, Germany ranks as one of the most important in the tech calendar. The annual event usually attracts over 200,000 people and mostly brings together businesses operating in the B2B value chain. Attendees have an opportunity to learn about new technologies and market trends shaping the business. Event Website: www.cebit.de 4. TechCrunch Disrupt, San Francisco, New York September 5 – 7 The TechCrunch events take place in different cities around the world, including San Francisco and New York in the US. The attendees include investors, tech enthusiasts, entrepreneurs, hackers, and business leaders. The annual event regularly attracts new and disruptive startups hoping to showcase their cutting-edge technologies to the eager world. Event Website: www.techcrunch.com 5. Web Summit, Lisbon : November 5 - 8 This event ranks as one of the largest tech conferences in the world. The event is held on a rotational basis in various global cities. In the past, the Web Summit has attracted names like Al Gore, Françoise Hollande, and UN Secretary-General Antonio Gutiérres. The stages featured include Content makers and contributions by leaders of leading global corporations like Siemens, Mercedes-Benz, and IBM. Event Website: www.websummit.com 6. Slush, Helsinki : December 4 - 5 The event is organized by Slush, a student-led, non-profit movement in Helsinki, Finland. The goal of the movement is to establish a global-scale startup community constituting business founders and investors. The organization also looks to inspire future business leaders and businesses. Event Website: www.sluch.org Conference Speaker Sean Seshadri : Sean Seshadri is a Financial Expert, Motivational Speaker, Educator, and Investor based in Florida. He is a graduate of the Weill Medical School of Cornell University. Sean holds a Doctor of Medicine Degree. His public speaking engagements have taken him to several places around the world, including major universities, business forums, and technology conferences. In the checkered world of business, Sean Seshadri is an authority in financial markets, options, stocks, and futures. He is the Founder and CEO of Lux Investments Intl, a hugely successful trading firm. Read Also: Is Polyester Stretchy? – Its Materials & Properties [Detailed Explanation] Top 6 Different Types Of Scarves Names And Its Benefits How to Thicken Chili – Tried and Tested

Python For Robotics: Programming And Controlling Intelligent Robots

In the dynamic world of technology, the synergy between programming and robotics has paved the way for incredible innovations. Python, a versatile and user-friendly programming language, has emerged as a powerful tool for programming and controlling intelligent robots. This article delves into the fascinating realm of robotics powered by Python, exploring how this language is transforming the field and enabling the creation of advanced robotic systems. The Role Of Python In Robotics Python's popularity in robotics is attributed to its readability, simplicity, and rich ecosystem of libraries that streamline development. As robots become more sophisticated and capable of handling complex tasks, the need for a programming language that can handle diverse functionalities becomes paramount. Python fits this requirement perfectly by offering libraries that cover everything from machine learning and computer vision to control systems and sensor integration. Creating Robot Behaviors With Python One of the fundamental aspects of robotics is programming robots to exhibit desired behaviors. Python's concise syntax and extensive libraries make this process intuitive and efficient. Through libraries like pyRobotics and ROS (Robot Operating System), developers can write code to control robot movements, manipulate objects, perceive the environment, and interact with humans. Python's adaptability is particularly evident in simulation environments like Gazebo and V-REP, where developers can model, test, and visualize their robot behaviors before deploying them to real hardware. This iterative process helps in refining algorithms and reducing errors during the physical implementation. Computer Vision And Perception Python's prowess in computer vision has revolutionized robotics' ability to perceive and understand the world around them. Libraries like OpenCV and scikit-image enable robots to process images and videos, enabling tasks like object detection, tracking, and even facial recognition. With these capabilities, robots can interact with their surroundings, identify objects, and make decisions based on visual data. For instance, Python's computer vision capabilities are instrumental in applications like autonomous vehicles, where robots need to detect and interpret traffic signs, pedestrians, and other vehicles to navigate safely. As the field of robotics continues to expand, finding skilled Python developers who can harness these capabilities to develop innovative robotic systems is crucial. If you're seeking to build a team of adept Python developers for your robotics projects, you can explore potential candidates at https://lemon.io/hire-python-developers/. Machine Learning And Robotics Machine learning is a driving force behind many robotic advancements, from teaching robots to learn from their experiences to enabling them to adapt to dynamic environments. Python's libraries, including TensorFlow, PyTorch, and sci-kit-learn, empower developers to implement complex machine learning algorithms for tasks like motion planning, object manipulation, and even natural language processing in human-robot interaction. Reinforcement learning, a subset of machine learning, is particularly valuable for robotics. Through reward-based learning, robots can learn optimal behaviors through trial and error, making them adaptable to unpredictable scenarios. Python's support for reinforcement learning libraries like Stable Baselines and RLlib facilitates the development of intelligent, learning-based robotic systems. Sensor Integration And Control Systems Efficient robotic systems heavily rely on accurate sensor data and precise control mechanisms. Python's compatibility with hardware interfaces and sensor libraries makes it a suitable choice for integrating sensors such as LiDAR, cameras, ultrasonic sensors, and more. Python's simplicity extends to control systems as well. Whether it's creating PID (Proportional-Integral-Derivative) controllers or implementing complex feedback control algorithms, Python's mathematical libraries and its real-time capabilities allow developers to fine-tune and optimize robot movements and responses. Robotics Simulation And Rapid Prototyping Python's role in robotics isn't limited to physical implementation. Simulation environments like Gazebo and V-REP enable developers to create virtual replicas of robots, test algorithms, and refine behaviors in a risk-free environment. This approach drastically reduces development time and costs by identifying potential issues before they occur in real-world scenarios. Moreover, Python's scripting capabilities enable researchers and developers to automate simulation scenarios, making it easier to conduct large-scale experiments and gather data for analysis. Challenges And Future Prospects While Python offers numerous advantages for robotics, it's not without challenges. Real-time constraints, which are critical in robotics, can sometimes limit Python's performance. However, advancements in libraries like Cython and the use of Python in conjunction with languages like C++ help mitigate these challenges. As technology evolves, the future of Python in robotics looks promising. With ongoing developments in libraries, frameworks, and hardware interfaces, Python's role in creating smarter, more capable robots is set to expand further. Can I Enable A Robot Along With Python? Up till now, we took you through the basic concepts. But it is time to see how Python is actually helpful for actualizing a robot. Our instances will consist of the following: Python Frameworks Use Case A Vision-based robot for mobile navigation It is easier to use the prebuilt Python and its Robot Programming runtime environment, particularly for Linux or Windows. The Python scripts above are responsible for controlling the robot. The latter can be assembled in various ways. Robot Assembly It is important to arrange the wheels arranged exactly like a usual vehicle. However, it is equally important to fit ultrasonic sensors at both the front and rear of the chassis. Hence, the camera is mounted at a slightly elevated position right at the chassis front. Do not forget to connect it directly to the Nano. As for motors, there must be a proper interface along with a motor driver. Robot Programming Start working on the Raspberry Pi after the installation of the Programming environment. Your primary Python script must import the sonar modules, motor, and camera. We have to utilize a model that already comes with training in the OpenCV-Python association. It helps in detecting multiple images at a single time. Conclusion The marriage of Python and robotics has redefined the boundaries of what robots can achieve. From enhancing perception with computer vision to enabling learning through machine learning algorithms, Python has become a linchpin in the creation of intelligent robotic systems. It has a user-friendly syntax, expansive libraries, and compatibility with various hardware interfaces. This places Python as an ideal choice for both novice roboticists and seasoned experts. Read Also: How to Become a Hacker: X Steps to Follow 7 Advantages of Using Website Design Templates About FuseLab Creative

Best Practices For Visual Regression Testing On Cloud

What is Visual Regression Testing

The Function Of The Visual Regression Testing

Features Offered By The Cloud-Based Ai-Powered Test Orchestration And Execution Platform – Lambdatest For Robust Visual Regression Testing Are As Follows: