1. What is App Modernization?
2. Types of App Modernization
3. Role of Automated Testing in App Modernization
4. Automation Testing Tools & Frameworks for App Modernization
5. How to Choose the Right Automated Testing Tool?
6. Conclusion
7. How Can TestingXperts Help with Automated Testing for App Modernization?

What is App Modernization?

App Modernization refers to updating older software applications with modern architectures, features, and capabilities, ensuring they remain relevant and efficient in contemporary IT environments. It encompasses many activities, from simple code refactoring to replacing legacy systems entirely.

The digital landscape is evolving at a remarkable rate. With over 87% of enterprises reporting digital disruptions challenging their business models, there’s a pressing need to adapt and transform. Here’s why modernization is so essential:

Stay Competitive:

Modern applications cater to current market expectations, ensuring businesses remain relevant in the eyes of customers and stakeholders. According to a study, companies that fail to modernize risk falling 20% behind their competitors in revenue and customer satisfaction.

Optimize Costs:

Legacy systems, although familiar, can be expensive to maintain. Upkeeping outdated software drains resources, while modern apps can reduce operational costs by up to 25%, enhancing ROI.

Scalability & Flexibility:

Modern applications are designed to scale with growing business demands. They offer flexibility, ensuring businesses can quickly pivot in response to changing market dynamics.

Enhanced Security:

As cyber threats become increasingly sophisticated, outdated software becomes more vulnerable. Modernized apps incorporate the latest security measures, protecting valuable business data from breaches.

Types of App Modernization

App modernization is a comprehensive process that involves updating and improving software applications to enhance performance, security, and adaptability in today’s technological landscape. As technologies evolve, businesses need various methods to update their software based on specific needs and objectives. Let’s explore the different modernization techniques to determine which might be optimal for varying scenarios:

Re-hosting & Re-platforming:

Re-hosting is about taking an app from one environment and moving it to another, like from an in-house server to the cloud. It doesn’t change how the app looks or works but where it’s located. Re-platforming means making changes for apps to perform better in their new environment without altering their core functions.

Refactoring & Re-architecting:

Refactoring is making small changes in the software to improve its performance or clarity without changing what it does. Re-architecting means restructuring the app, changing how it works internally to make it more efficient or to add new features.

Rebuilding & Replacing:

Rebuilding means making the app again from scratch using modern methods and technologies. Replacing means buying or adopting a new app to replace the outdated one.

Every business is different, and there’s no one-size-fits-all answer. When deciding on a modernization approach, companies should consider their goals, budget, and how crucial the app is to their operations. For some, a simple re-host might be enough. Others might benefit from a complete rebuild. It is essential to evaluate the needs, consult with IT experts, and choose a path that aligns with the business’s future vision.

Automated Testing: A Deeper Dive

In the context of app modernization, the efficacy of the updated software is paramount. Automated Testing, an integral aspect of modern software development, employs specialized tools and software for comprehensive testing procedures. This approach not only assures the quality of the software but also streamlines the deployment process.

Why Manual Testing Isn’t Enough in Modernization?

While manual testing offers the advantage of human intuition, its scalability and efficiency in the face of complex modernized applications are limited. Applications today can encompass extensive lines of code, making exhaustive manual testing cumbersome and less precise. Automated Testing provides a systematic and swift alternative, enabling thorough verification of modernized applications to ensure optimal performance.

Continuous Integration and Continuous Deployment in Modernization

CI/CD displays modern software development characteristics. CI represents the frequent integration and testing of code changes, while CD ensures that these validated changes are promptly deployed. Automated Testing is foundational to this framework, facilitating rapid and reliable assessments and enabling businesses to deploy updates with greater frequency and confidence.

Role of Automated Testing in App Modernization

Ensuring the new version works perfectly when updating old software is crucial. That’s where Automated Testing comes in. It checks every part of the software to ensure it’s functioning correctly and is secure. Let’s explore how Automated Testing helps when modernizing apps:

Ensuring Seamless Transition:

When businesses update their software, they must test it to ensure a smooth transition. Automated Testing does this quickly and thoroughly. It checks the new software, finds problems, and ensures that the transition from old to new is smooth, with no major errors.

Reducing Errors and Reworks:

Mistakes can be expensive. If a business launches updated software with issues, fixing them later can cost time and money. Automated testing detects these issues early on. By catching problems before they reach users, businesses can save money on fixing issues and avoid the costs of unhappy customers.

Improving Time-to-Market:

In the business world, time is money. Getting updated software to customers faster can be a significant advantage. Automated Testing speeds things up. Instead of waiting for humans to check everything manually, a computer program quickly tests the software. This means businesses can launch their modernized apps faster and stay ahead of the competition.

Building Trust in Modernized Apps:

People trust brands that offer quality. When businesses update their software, they want users to trust the new version. Automated Testing helps with this. Thoroughly checking the software ensures that the updated app is of high quality. So, when users use it, they can be confident that it will work well.

Automation Testing Tools & Frameworks for App Modernization

As app modernization becomes necessary, the right automated testing tools and frameworks become essential to ensure the revamped software meets quality standards. These tools simplify the testing process and seamlessly integrate with modern development practices, making them a vital aspect of the modernization process. Here’s a list of some of the automated testing tools:

Selenium:

Selenium, an open-source tool, has gained popularity among testers for its flexibility and wide range of capabilities. It allows testing of web applications across various browsers, ensuring that the modernized application performs uniformly across platforms. The tool’s versatility, backed by a supportive community and rich documentation, makes it an ideal choice for many businesses venturing into app modernization.

Appium:

With the surge in mobile app usage, testing mobile apps for functionality and user experience is crucial. Appium is an open-source platform that enables automated testing on iOS and Android platforms, regardless of the native, mobile-web, or hybrid application type. Its ability to write tests in multiple programming languages further underscores its adaptability and broad reach.

TestNG & JUnit:

Frameworks like TestNG and JUnit have reshaped how developers approach testing in the Java environment. TestNG, inspired by JUnit, offers enhanced functionalities like grouping, sequencing, and parallelizing tests, ensuring a structured and comprehensive testing process. On the other hand, JUnit is known for its simplicity and annotations-driven approach, making it a staple in many modernized application testing scenarios.

Jenkins:

It’s an open-source tool that facilitates the automation of various stages in the development pipeline, including testing. Integrating seamlessly with various testing tools, Jenkins accelerates the feedback loop, allowing developers to address real-time issues essential for apps undergoing modernization.

How to Choose the Right Automated Testing Tool?

The key to making an informed choice lies in aligning the tool’s capabilities with the project’s specific requirements. This section provides a roadmap for businesses to determine which tool best aligns with their app modernization objectives.

Understanding Application’s Architecture:

Before starting with tool selection, it’s crucial to understand the application’s architecture undergoing modernizing. Is it a web application, a mobile app, or a desktop application? Different tools are optimized for different platforms. For instance, while Selenium excels in web application testing, Appium is tailored for mobile environments.

Integration with Existing Systems:

Consider how well the testing tool integrates with existing systems. A tool seamlessly integrating with your current development environment, version control system, and CI/CD pipeline can streamline the testing process, reduce manual interventions, and increase efficiency.

Flexibility and Scalability:

Modernized applications often evolve, adding new features and functionalities. The chosen testing tool should be flexible and scalable to accommodate this growth. It should allow testers to quickly modify, expand, or reduce tests’ scope without substantial rework.

Language and Framework Support:

The programming languages and frameworks the team is familiar with should be considered significantly. If the team is well-versed in Java, tools that support Java will have a shorter learning curve. Similarly, if an app is built on a specific framework, ensuring the tool that supports that framework can be beneficial.

Cost Implications:

While open-source tools come without licensing fees, it’s essential to consider the total cost of ownership. It includes training, maintenance, integration, and potential downtime costs. Sometimes, investing in a paid tool with premium support and features can be more cost-effective in the long run.

Performance and Reporting Capabilities:

Real-time feedback and comprehensive reports are vital to understanding the efficacy of tests. A tool that provides detailed logs, visual reports, and real-time alerts can help teams quickly identify issues and improve the quality of the modernized app.

Conclusion

The digital realm constantly evolves, with innovations and technologies reshaping how businesses operate and deliver value. In this dynamic environment, app modernization has become necessary for any organization to stay relevant and competitive. With its efficiency and precision, automated testing is essential for businesses. Businesses can confidently leverage new opportunities and tackle emerging challenges by ensuring modernized apps function optimally and meet quality standards.

How Can TestingXperts Help with Automated Testing for App Modernization?

In the evolving digital landscape, app modernization helps businesses to progress, offering them a way to remain agile, relevant, and ahead of the competition. Automated testing ensures that revamped applications meet and exceed quality benchmarks. At TestingXperts, we deliver top-notch automated testing solutions tailored for app modernization, ensuring your software is robust, efficient, and future-ready. Here’s why you should partner with TestingXperts for app modernization services:

• We utilize cutting-edge tools and methodologies for accurate testing

• Comprehensive testing expertise across web, mobile, and desktop platforms

• Seamless integration with continuous integration and continuous deployment pipelines

• Tailored solutions aligning with specific app modernization objectives

• Proactive monitoring and real-time feedback for early issue identification

• Commitment to continuous learning, ensuring alignment with the latest trends and best practices

• To know more, contact our QA experts now.

The post Importance of Automated Testing in App Modernization first appeared on TestingXperts.

1. Why Implement a Proof of Concept in Automation Testing
2. Planning and Preparation for PoC in Automation Testing
3. Choosing the Right Tools and Technologies
4. Best Practices and Tips for Successful PoC Implementation
5. Conclusion
6. How Can TestingXperts help you?

Automation Testing is leading modern software development, empowering teams to accelerate testing processes, enhance efficiency, and ensure impeccable software quality. It’s the art of leveraging technology to conduct tests, make data-driven decisions, and ultimately, deliver superior software products to the market.

Proof of Concept (PoC) stands as a guiding light of assurance and innovation. It’s the preliminary step, a glimpse into the future of automation testing, where ideas are validated, strategies are fine-tuned, and the potential of automation is vividly illustrated. PoC is not just a test; it’s an exploration, a prototype that showcases the transformative power of automation.

Why Implement a Proof of Concept in Automation Testing

Proof of Concept (PoC) plays a pivotal role in any innovative venture, serving as a crucial phase before full-scale implementation. Here’s why incorporating a Proof of Concept in automation testing can prove to be very important in the world of technological advancements:

Validating Feasibility

The first and foremost purpose of a Proof of Concept is to validate the feasibility and viability of an idea or concept. It provides a small-scale test environment to experiment with the concept in a controlled setting. By doing so, you can ascertain if the envisioned solution is technologically and practically possible. It’s akin to dipping a toe in the water before taking the plunge—minimizing risks and ensuring that resources are allocated to projects that hold promise and align with your business goals.

Demonstrating Value

Beyond feasibility, a PoC allows you to showcase the value proposition of your idea. It provides a tangible representation of what the product could achieve, allowing stakeholders to comprehend the potential benefits. This demonstration is instrumental in gaining buy-in from decision-makers, investors, and end-users. A well-executed PoC not only reveals the value of the solution but also instills confidence in the minds of stakeholders, fostering enthusiasm and support for the project. It’s the bridge that connects imagination to reality, ensuring that the value of an idea is clearly communicated and understood.

Planning and Preparation for PoC in Automation Testing

The success of a Proof of Concept (PoC) hinges on meticulous planning and thorough preparation. Let’s delve into the crucial aspects of planning and preparation for a PoC:

Defining Objectives

Before embarking on a PoC, it’s imperative to have clear and well-defined objectives. What do you aim to achieve with this PoC? These objectives should align with the broader goals of the project or initiative. Whether it’s testing a new technology, evaluating a specific feature, or proving a concept’s feasibility, outlining these objectives will provide a roadmap for the PoC. Clear objectives ensure that the effort is focused, and the outcomes are measured against predetermined criteria.

Resource Allocation

Resource allocation is a critical step in planning a successful PoC. This includes assigning the right people with the necessary skill sets to execute the PoC effectively. It also involves providing the required budget, tools, and time for the PoC to be conducted seamlessly. Adequate resourcing ensures that the team can work efficiently and achieve the set objectives within the defined timelines. It’s about putting the right pieces in place to make the PoC a meaningful and impactful exercise.

Infrastructure Requirements

Understanding and establishing the necessary infrastructure for the PoC is vital. This could encompass hardware, software, networking, and any other technological prerequisites. Ensure that the infrastructure mimics the intended real-world scenario as closely as possible to achieve accurate and relevant results. Additionally, consider scalability, flexibility, and security aspects while defining the infrastructure requirements. A well-planned infrastructure sets the stage for a smooth execution of the PoC, providing the foundation for thorough testing and validation. Here is the list of a few tools you can consider:

Choosing the Right Tools and Technologies

The choice of tools should align with your project’s goals, team expertise, and the technologies you are testing. The PoC phase is an excellent opportunity to evaluate and experiment with different tools to determine which ones best suit your long-term automation testing needs.

Selenium WebDriver (Script-Based)

Selenium WebDriver is a popular open-source tool for automating web applications. It provides a script-based approach to automation, allowing testers to write automation scripts in programming languages such as Java, Python, C#, and more. Selenium supports multiple web browsers and provides extensive flexibility for test automation.

Test Project (Low Code and No-code)

TestProject is a comprehensive test automation platform that offers both low-code and no-code capabilities. It provides a user-friendly, web-based interface for test creation, making it accessible to both technical and non-technical users. Testers can create automation tests visually with no coding or enhance them with scripting using Selenium and Appium.

Katalon Studio (Low-Code and Script-Based)

Katalon Studio is a test automation tool that combines low-code and script-based automation. It offers a user-friendly interface for creating test cases without extensive coding. While Katalon Studio simplifies automation for beginners with its low-code features, it also allows experienced testers to write scripts using Groovy or Java for more complex scenarios.

Tricentis Tosca (Script-Based and Low-Code)

Tricentis Tosca is an enterprise test automation platform that supports both script-based and low-code automation. It enables testers to create automation scripts in a variety of programming languages. Tosca also offers a low-code interface, making test case design more accessible to non-developers. It focuses on end-to-end test automation and integrates with various technologies and applications.

TestCraft (No-Code)

TestCraft is a no-code test automation platform designed for testers and non-technical users. It provides a visual, drag-and-drop interface for test creation, allowing users to create automation tests without writing any code. TestCraft specializes in web application automation and supports various browsers.

Best Practices and Tips for Successful PoC Implementation

Implementing a successful Proof of Concept (PoC) requires adherence to best practices and learning from experiences. Here are key considerations and lessons learned for a fruitful PoC implementation:

Key Considerations:

Clearly Defined Objectives and Scope:

Start by articulating clear objectives for your PoC. What do you aim to achieve, prove, or validate with this PoC? Without well-defined objectives, you risk losing focus and not effectively demonstrating the value of the proposed solution. Success criteria should be specific and measurable. For example, if you’re testing an automation tool, a success criterion might be a 20% reduction in test execution time.

Realistic Timeline and Milestones:

Assemble a team with a mix of skills and expertise relevant to the PoC. Include individuals who are well-versed in the subject matter and those who can provide fresh perspectives. Team members should have a good understanding of the project’s goals and be capable of working collaboratively. A diverse team can offer varied viewpoints and enhance problem-solving.

Use Real-World Data and Scenarios:

To make the PoC as realistic as possible, utilize actual data and real-world scenarios that mirror the environment where the solution will be implemented. Using synthetic or idealized data can skew results and lead to inaccurate conclusions. Real-world data and scenarios help in identifying potential issues, and any feedback derived is more applicable to practical situations.

Plan for scalability:

Even though the PoC is relatively small in scope, consider how the solution will scale if you decide to implement it on a broader scale. Evaluate the scalability of the solution in terms of performance, resource requirements, and ease of expansion. Assessing scalability during the PoC helps avoid future challenges when moving to a larger deployment.

Consider Long-Term Maintenance and Support:

While focusing on the PoC, don’t overlook the long-term maintenance and support aspects. Consider how easy it will be to maintain the solution, apply updates, and provide ongoing support. Factor in costs and resources needed for these activities when evaluating the viability of the solution.

Conclusion

Implementing a Proof of Concept (PoC) in automation testing is a strategic step that demands careful planning, precise execution, and a commitment to learning from the process. By following key considerations such as defining clear objectives, creating realistic timelines, involving diverse stakeholders, and employing a data-driven approach, organizations can ensure a solid foundation for their PoC.

Remember, a well-executed PoC not only validates the feasibility and value of an automation testing strategy but also provides valuable insights that steer decision-making and set the course for successful automation implementations. With a focused approach and a mindset of continuous improvement, PoCs in automation testing can drive innovation, elevate product quality, and contribute to achieving organizational excellence in the dynamic world of software development and testing.

How Can TestingXperts help you?

TestingXperts excels in assisting you throughout the implementation of a Proof of Concept (PoC) in Automation Testing. Our dedicated team collaborates closely with you to understand your specific testing needs and objectives. Leveraging our extensive expertise in automation testing and a wide range of tools, we craft a tailored PoC strategy aligned with your project requirements. We guide you in selecting the most suitable automation tools and technologies for your PoC, ensuring seamless integration with your existing systems. Throughout the PoC execution, we meticulously design and execute test cases, analyze results, and provide detailed reports with valuable insights. Our goal is to empower you to make informed decisions and pave the way for a successful transition from PoC to a robust, scalable automation strategy. With TestingXperts by your side, you’re poised to achieve efficiency, accuracy, and enhanced quality in your automation testing endeavors.

The post How to Implement Proof of Concept in Automation Testing first appeared on TestingXperts.

Codeless automation testing represents a streamlined approach to automation testing, eliminating the need for script writing. Crafting automation scripts can pose significant challenges for QA engineers, as it demands writing code in various programming languages, which is both demanding and time intensive. By adopting codeless automated testing, you can drastically reduce testing time, particularly for repetitive test cases, all without the need for coding.

Codeless Automation Testing

In the era of codeless testing tools available in the market, you’ll find a range of user-friendly features that simplify the testing process. These include:

– Intuitive Drag and Drop Interface.

– Efficient Record and Playback Functionality.

– Seamless Integrations with Machine Learning (ML) or Artificial Intelligence (AI) technologies.

– Reduced Maintenance Efforts.

This approach not only accelerates testing but also ensures that the testing process remains accessible and efficient, even for testers without extensive coding experience.

How does Codeless Automation Testing Work?

Codeless automation testing, also known as no-code/low-code testing, involves using tools and platforms that allow individuals to create automated tests without writing traditional lines of code. This approach enables testers and non-technical users to design and execute test cases using a graphical user interface (GUI) or a simple scripting language, eliminating the need for programming expertise.

Here’s an overview of how codeless automation testing works:

Intuitive Test Scenario Design:

Codeless automation testing starts with the development of intuitive and easily understandable test scenarios. Testers use a visual interface, often equipped with drag-and-drop features and a palette of predefined testing actions. The intuitive design of the interface allows testers to select actions that simulate user interactions with the application, arranging them in the desired order to construct a logical test flow.

Element Identification and Interaction:

Within the codeless testing tool, testers can easily identify and interact with elements of the application under test (AUT). Through the graphical interface, testers can select various elements such as buttons, input fields, dropdowns, and other user interface components without requiring any programming knowledge. This allows for simulating user actions like clicks, input entries, and navigations.

Intelligent Validation and Assertions:

During the creation of test scenarios, testers define validation points and assertions within the test steps. These validation points are critical for verifying the correctness of the application’s behavior. The tool provides predefined validation options and allows testers to set conditions and expectations. Assertions aid in ensuring that the application meets the desired criteria and functions as intended.

Parameterization and Data-Driven Testing:

Codeless automation testing enables parameterization, where testers can input data directly into the test steps. This could be either manually entered data or sourced from predefined datasets. The ability to use different sets of test data allows for data-driven testing, helping verify the application’s behavior under various conditions and inputs.

Efficient Test Execution and Reporting:

Once the test scenarios are created and configured, testers can initiate the execution of the automated tests directly from the codeless testing tool. The tool executes the defined test steps, interacts with the application based on the specified actions, validates the outcomes, and generates detailed reports. These reports include information on test execution status, duration, pass/fail results, and any encountered issues. The generated reports are valuable for identifying potential defects and providing insights into the application’s quality.

Significance of Choosing the Right Codeless Automation Testing Tool

Selecting the right codeless automation tool holds immense significance in the realm of software testing and quality assurance. Here’s why making this choice wisely is crucial:

Efficiency and Productivity:

The right codeless automation tool streamlines test case creation and execution. It empowers testers to design and execute tests swiftly through user-friendly interfaces, saving a significant amount of time and effort. This efficiency boost is particularly valuable in fast-paced development environments.

Reduced Learning Curve:

Codeless tools are designed to be intuitive, making them accessible to a broader range of team members, including those without coding skills. This reduces the learning curve and allows for easier onboarding of new team members, ultimately saving time and resources.

Cost-Effective:

Investing in the right codeless automation tool can be cost-effective in the long run. It minimizes the need for hiring specialized automation engineers and reduces the maintenance overhead associated with traditional scripted automation.

Flexibility and Scalability:

The ideal codeless tool offers flexibility to adapt to evolving testing needs. It should be capable of handling a variety of test scenarios and be scalable to accommodate the growth of your project.

Reliability and Robustness:

Your chosen tool should provide reliable and robust testing capabilities. This means it should support various testing types, handle complex scenarios, and generate dependable test results.

Integration Capabilities:

Integration with your existing development and continuous integration/continuous deployment (CI/CD) tools is crucial. A well-chosen tool seamlessly integrates with your workflow, enhancing the overall efficiency of your software development process.

Support and Community:

The availability of a strong user community and reliable customer support for the tool is vital. This ensures that you have resources and assistance readily available when encountering challenges or seeking to optimize your testing processes.

In essence, the right codeless automation tool can be a game-changer, enabling your QA team to deliver higher-quality software in less time, all while enhancing collaboration and reducing the complexities associated with traditional script-based automation. It’s a strategic decision that can significantly impact your software development lifecycle for the better.

List of Features to Look for in a Codeless Test Automation Tools:

Application development firms increasingly embrace codeless test automation tools to keep up with the rapid cadence of new product releases within their CI/CD pipelines. Consequently, they can significantly reduce both the expenses and the time required for repetitive testing, all without the necessity of manual code creation.

In the midst of the continuously rising popularity of codeless test automation, the market boasts an array of over a dozen automated testing tools to consider. Nevertheless, it’s important to discern that not all these tools meet the criteria of being labeled as “genuine” codeless test automation solutions. To help with your selection, here are key features to seek in a codeless test automation tool:

Is it capable of performing resource-intensive and costly tests without requiring proficiency in a specific programming language?

– Does it facilitate application testing on a variety of devices and operating systems?

– Does it offer a straightforward and user-friendly interface, akin to an “Action Logic Editor”?

– Does it come with features for “In-Sprint and Self-healing” capabilities?

– Does it support seamless integration with AI and machine learning technologies?

Does it offer unified automation capabilities spanning various platforms, encompassing Web and Mobile applications, APIs, Desktop applications, and Mainframes?

Let’s take a closer look at the top five codeless test automation tools available for your testing needs:

Top Four Codeless Automation Testing Tools 

UiPath

UiPath is a leading robotic process automation (RPA) platform that has gained prominence in the automation landscape for its user-friendly and codeless automation capabilities. Codeless automation, sometimes referred to as “low code” automation, is a significant advantage of UiPath, as it allows individuals with limited programming experience to create and deploy automated workflows efficiently.

Its user-friendly interface, extensive library of activities, and commitment to scalability and security make it a powerful tool for both beginners and experienced automation professionals. By enabling users to automate without extensive coding, UiPath empowers organizations to achieve greater efficiency and productivity in their day-to-day operations.

Here are some of the core features of the tool:

– It allows users with limited or no coding experience to create automation processes.

– Provides a library of pre-built automation activities for various tasks.

– Create and reuse custom workflows and activities, promoting efficiency.

– Includes debugging and testing capabilities for identifying and fixing issues in workflows.

– Supports integration with APIs, databases, and web services to enhance automation. Enables organizations to start small and scale automation efforts as needed.

Katalon Studio

Katalon Studio stands as one of the foremost codeless test automation tools, providing a spectrum of testing capabilities encompassing APIs, web applications, and desktop applications.

This tool is designed for accessibility, catering to both novice and seasoned software testers alike. It boasts a user-friendly interface equipped with features like record and play, along with a drag-and-drop editor. Furthermore, software testers have the flexibility to seamlessly integrate external libraries into Katalon Studio, simplifying test execution without the need to build the framework from the ground up.

Here are some of the core features of the tool:

– Included are pre-designed project templates, test case libraries, and object repositories.

– Enhanced collaboration capabilities for agile teams through integrations with platforms like Slack, GitHub, and others.

– Empowers technical users to craft advanced automation scripts utilizing Selenium or JavaScript.

– Enables the incorporation of native plugins for continuous integration.

– Offers an array of extensive reporting functionalities.

TOSCA

Test Orchestration, Automation, and Reporting,” is a comprehensive test automation tool that offers codeless automation capabilities. Codeless automation is a paradigm shift in the world of software testing, enabling testers and quality assurance professionals to create and execute test automation scenarios without writing complex code scripts.

TOSCA has gained popularity for its user-friendly, codeless approach to test automation, making it accessible to a broader range of professionals, including those without extensive coding skills. TOSCA as a codeless automation tool offers a powerful solution for organizations looking to accelerate their test automation efforts while minimizing the reliance on coding expertise. Its intuitive interface, extensive integration options, and focus on reusability make it an attractive choice for teams seeking efficient and effective test automation.

Here are some of the core features of the tool:

– Utilizes keywords to abstract and simplify test case creation and management.

– Encourages the reuse of test modules, test cases, and components for efficient automation.

– Offers extensive integrations with various tools and technologies, including test management systems and CI/CD pipelines.

– Generates comprehensive test execution reports and provides analytics on test results.

– Facilitates efficient regression testing to catch and prevent software regressions.

TestIM

Testim is an all-encompassing AI-driven testing platform that assists teams in automating tests with ease, reliability, and collaborative efficiency. Leveraging dynamic and intelligent locators, Testim adeptly adapts to alterations within the Application Under Test (AUT), autonomously generating and executing tests. Furthermore, this platform harnesses the power of machine learning to craft, conduct, and oversee tests, leading to a substantial reduction in the time required for test creation and execution, with the capability to simultaneously perform thousands of tests.

Features:

– Testim’s intelligent and adaptable locators automatically generate tests, simplifying the process of keeping pace with rapid releases and UI modifications for teams.

– It seamlessly integrates with your existing CI/CD pipelines and collaboration tools.

– With Testim’s visual test editors, test creation becomes effortless, catering to both technical and non-technical team members.

– The platform provides comprehensive test reports and robust bug checkers, facilitating comprehensive test analysis.

Conclusion

In conclusion, as we step into 2023, the landscape of software testing is rapidly evolving, and codeless automation testing tools are at the forefront of this transformation. These tools are reshaping how testing is conducted, making it more accessible, efficient, and collaborative for teams across various domains and industries.

While the list provided here showcases some of the leading options available, it’s essential to remember that the right tool for your organization depends on factors like your project requirements, team expertise, and budget. Therefore, it’s advisable to evaluate these tools thoroughly and consider how they align with your testing objectives before making a decision.

Codeless automation tools are not only streamlining the testing process but also contributing to the broader goals of achieving faster time-to-market, ensuring software quality, and enhancing collaboration between development and QA teams. Embracing these tools in your testing strategy can give your organization a competitive edge in delivering high-quality software products that meet user expectations in the dynamic landscape of 2023 and beyond.

Should you want any Codeless automation testing services, let’s connect and discuss how TestingXperts can help your business!

The post Top Codeless Automation Testing Tools for 2023 first appeared on TestingXperts.

1. What is Low Code?
2. Introduction to Low-code Test Automation
3. Benefits of Low-code Test Automation
4. Popular Low-code Test Automation Tools
5. Limitations of Low-code Test Automation
6. Where is Low-code Application Testing Used?
7. Real-World Examples of Low Code Test Automation
8. Conclusion
9. Why Choose TestingXperts for Low-code Testing?

According to projections by the U.S. Department of Labor, the global shortage of software engineers could reach a staggering 85 million by 2030. And in a world where software development cycles are shrinking, organizations face increasing pressure to deliver high-quality applications quickly. This demand for agility has led to the rise of low code development, a methodology that allows applications to be built rapidly with minimal hand-coding.

As technology continues to evolve, traditional software development practices often struggle to keep up with the demands of modern businesses. Low code development is an approach that allows applications to be created with minimal hand-coding, empowering developers to build applications using intuitive drag-and-drop interfaces and pre-built components visually. It offers a faster and more efficient way to develop software, enabling organizations to meet the growing demand for innovative applications.

What is Low Code?

Before starting with low code test automation, let us understand what low code is. Low code is a methodology that enables application development and testing with minimal traditional coding. Instead of writing lines of complex code, low code platforms offer intuitive visual interfaces and pre-built components, allowing developers to design and assemble applications rapidly.

This approach allows businesses, users, and professional developers to collaborate in building applications. It reduces the time and effort required for development, enabling faster iterations and more responsive solutions. Low-code platforms bridge the gap between business requirements and IT capabilities by leveraging drag-and-drop interfaces, pre-defined logic, and visual workflows.

Introduction to Low-code Test Automation

Now that we have a basic understanding of low code, let us understand the relationship between low code and test automation. Low code test automation combines the benefits of low code development with the power of automation to streamline the software testing process.

Traditionally, testing applications have been time-consuming and labor-intensive, often prone to human error. However, with low code test automation, organizations can automate the testing process, significantly reducing manual effort and ensuring consistent and reliable results. Organizations can use specialized tools and frameworks to build automated test suites that execute test cases, simulate user interactions, and validate application functionality. This approach streamlines the testing efforts, improves efficiency, and enhances overall software quality.

Moreover, low code test automation fosters collaboration between development and testing teams. By aligning their efforts, teams can detect and resolve issues early in the development lifecycle, leading to faster bug fixes and improved overall application quality. This approach also facilitates rapid feedback loops, allowing teams to iterate quickly and deliver value to end users.

Benefits of Low-code Test Automation

Low-code test automation offers numerous benefits for organizations seeking to optimize software testing efforts. By combining the power of low code development and test automation, businesses can achieve significant productivity gains, improve test coverage, and enhance overall software quality. Following are some of the benefits you should know about:

Enhanced Test Coverage

Low code test automation enables organizations to achieve excellent test coverage, ensuring that critical scenarios and edge cases are thoroughly tested. Teams can allocate resources more efficiently by automating repetitive and time-consuming tasks like regression testing. This allows testers to focus on complex and exploratory testing, resulting in more comprehensive coverage and higher confidence in the application’s quality.

Reduced Manual Effort

One of the significant advantages of low code test automation is the reduction in manual testing efforts. Manual testing is prone to human error and can be time-consuming, leading to delays in the software development lifecycle. Organizations can automate repetitive testing tasks with low code test automation, reducing the dependency on manual efforts. This not only saves time but also improves the accuracy and consistency of the testing process.

Increased Efficiency and Productivity

Low code test automation significantly improves efficiency and productivity by automating the testing process. Testers can execute test cases more quickly and obtain faster feedback on application behavior. It enables faster bug detection and resolution, reducing the time required for software development cycles. With enhanced efficiency, development and testing teams can work together seamlessly, leading to streamlined collaboration and increased productivity.

Accelerated Time-to-Market

In today’s competitive landscape, time-to-market is critical for success. Low-code test automation helps accelerate software delivery by reducing testing cycles and eliminating bottlenecks. With faster and more efficient testing, organizations can expedite the release of high-quality applications. This allows businesses to seize market opportunities quickly, meet customer demands, and gain a competitive edge in their respective industries.

Improved Collaboration and Communication

Low code test automation fosters collaboration and communication between development and testing teams. By aligning their efforts, these teams can work together to identify and resolve issues early in the development lifecycle. This collaboration leads to faster bug fixes, improved overall application quality, and enhanced customer satisfaction. Additionally, low code test automation promotes rapid feedback loops, enabling iterative development and fostering a culture of continuous improvement.

Popular Low-code Test Automation Tools

When implementing low code test automation, having the right tools is crucial. Several low-code test automation tools are available, each offering unique features and capabilities. Let us look into some of these tools:

ACCELQ

It is a comprehensive low-code test automation platform designed to accelerate software testing. With its intuitive visual interface, ACCELQ enables testers to build and execute automated test cases without extensive coding. It offers codeless test automation, AI-powered self-healing tests, and robust reporting and analytics. ACCELQ empowers organizations to achieve faster test creation, execution, and maintenance, improving software quality.

Creatio

It is a low-code platform providing comprehensive application development and testing solutions. With its integrated low-code test automation capabilities, Creatio allows users to build and execute automated test cases seamlessly. It offers visual testing workflows, test script creation without coding, and efficient test execution across multiple environments. Creatio enables organizations to enhance the speed and quality of their application testing while maintaining a user-friendly low-code development environment.

Tricentis Tosca

It is a renowned low-code test automation tool that combines low-code development with comprehensive testing capabilities. It provides a unified platform for end-to-end test automation, including functional, regression, and performance testing. With Tricentis Tosca, organizations can leverage visual modelling and scriptless test automation to achieve efficient and scalable testing processes. The tool offers advanced features like risk-based testing, test data management, and integrations with popular test management tools.

Testsigma

It is a cloud-based low-code test automation platform that simplifies test automation for organizations. With its low code interface, Testsigma allows users to create and execute automated test cases without extensive programming knowledge. It offers codeless test creation, AI-powered self-healing tests, and seamless integration with popular CI/CD tools. Testsigma enables organizations to achieve faster time-to-market by streamlining their test automation efforts.

Katalon

It is a widely used low-code test automation tool that caters to organizations of all sizes. With its intuitive interface and robust automation capabilities, Katalon empowers testers to build and execute automated test cases efficiently. It offers many features, including scriptless test creation, data-driven testing, and integrations with popular CI/CD tools. Katalon simplifies the test automation process, enabling organizations to achieve faster releases and improved software quality.

Limitations of Low-code Test Automation

While low code test automation offers numerous benefits, it is essential to be aware of the challenges and limitations associated with this approach. Understanding these challenges will help you develop strategies to overcome them and maximize the effectiveness of your testing efforts:

Limited Customization Options

Low-code platforms often provide pre-built components and visual interfaces that simplify application development. However, this can sometimes limit the level of customization available for testing purposes. As a result, testers may face challenges when creating complex test scenarios or dealing with unique testing requirements. Evaluating the flexibility and extensibility of a low-code test automation tool is crucial to ensure it aligns with your specific testing needs.

Learning Curve and Skill Requirements

While low-code platforms aim to simplify the application development process, there is still a learning curve associated with mastering these tools. Testers and QA professionals may need to acquire new skills and undergo training to leverage low-code test automation effectively. It is essential to allocate time and resources for skill development and provide adequate training to ensure a smooth transition to the low code testing approach.

Compatibility and Integration Challenges

Integrating low code test automation tools with existing systems, frameworks, or test management tools can be challenging. Compatibility issues may arise when integrating low-code test automation with complex enterprise environments. Organizations need to carefully assess the compatibility and integration capabilities of their chosen low-code testing tool and ensure seamless collaboration with existing testing infrastructure.

Limitations in Test Coverage

While low code test automation can enhance test coverage, specific scenarios or edge cases may be challenging to automate. Complex business rules, advanced validations, or intricate data scenarios may require additional customization or coding, which may partially defeat the purpose of low-code test automation. Identifying such limitations early on and devising alternative strategies, such as leveraging code-based testing frameworks or hybrid approaches, is crucial to address these scenarios effectively.

Maintenance and Upgrades

Low-code test automation tools require regular maintenance and upgrades to keep pace with evolving technology and ensure optimal performance. As low-code platforms continue to grow, updates and new releases may introduce changes that affect existing test automation scripts or require adjustments. Testers must allocate resources and plan for ongoing maintenance and upgrades to ensure the long-term sustainability of their low code test automation efforts.

Where is Low-code Application Testing Used?

Low-code application testing has gained significant traction across various industries, offering organizations a powerful approach to enhance their software quality and delivery. Understanding the application of low-code testing in these sectors will provide valuable insights into its versatility and potential for success:

Finance

In the finance industry, where accuracy, security, and regulatory compliance are paramount, low-code application testing plays a crucial role. Financial institutions leverage low-code testing to ensure the reliability and integrity of their banking systems, investment platforms, and financial applications.

It enables thorough testing of critical functionalities such as transaction processing, data encryption, and user authentication. By employing low-code testing, finance organizations can streamline their testing processes, mitigate risks, and provide customers with secure and seamless digital experiences.

Retail

The retail industry relies heavily on technology to deliver exceptional customer experiences and drive sales. Low-code application testing helps retailers ensure the performance, usability, and reliability of their e-commerce platforms, inventory management systems, and customer relationship management (CRM) applications.

By thoroughly testing the checkout process, inventory updates, and user interactions, retailers can identify and resolve issues before they impact the customer experience. Low-code testing also enables retailers to adapt quickly to market demands, roll out new features, and stay competitive in the fast-paced retail landscape.

Insurance

In the insurance sector, low-code application testing enables organizations to validate the functionality and accuracy of their insurance systems, policy management platforms, and claims processing applications.

Through comprehensive testing, insurers can ensure that critical operations, such as underwriting, policy issuance, and claims handling, are error-free and efficient. Low-code testing allows insurers to simulate real-world scenarios, test complex calculations, and validate business rules, leading to improved accuracy, faster claims processing, and enhanced customer satisfaction.

Healthcare

Low-code application testing is paramount in the healthcare industry, where software reliability and patient safety are critical. Healthcare organizations leverage low-code testing to validate electronic health record (EHR) systems, medical imaging applications, telehealth platforms, and healthcare management solutions. By rigorously testing functionalities such as data integration, patient record management, and medical device interoperability, healthcare providers can ensure seamless and secure healthcare delivery. Low-code testing also helps organizations comply with industry regulations, protect patient privacy, and enhance the overall quality of care.

E-commerce

E-commerce platforms are the backbone of online businesses, and low-code application testing plays a vital role in ensuring their functionality, performance, and security. Organizations can thoroughly test features such as product catalog management, shopping cart functionality, payment gateways, and order processing by leveraging low-code testing. It helps identify and resolve user experience, transaction processing, and system integration issues. Low-code testing enables e-commerce businesses to deliver reliable and user-friendly online shopping experiences, increasing customer satisfaction and conversion rates.

Real-World Examples of Low Code Test Automation

Here are some real-world examples of how low code test automation is transforming software development:

Rapid Test Case Generation

Low code test automation tools leverage artificial intelligence and machine learning algorithms to automatically generate test cases based on the application’s user interface and business logic. This significantly speeds up the test design phase and reduces the effort required to create comprehensive test coverage.

Visual Test Scripting

With low code test automation, testers can create test scripts using a graphical interface, eliminating the need for traditional coding. This empowers business users and subject matter experts to contribute to the testing process without requiring programming skills. By visually representing the test scenarios, organizations can bridge the gap between technical and non-technical stakeholders, fostering collaboration and accelerating the feedback loop.

Cross-Platform Testing

Low code platforms often support multiple target platforms, such as web, mobile, and desktop applications. Testing these applications across various platforms can be time-consuming. Low-code test automation tools simplify this process by providing built-in cross-platform testing capabilities. Testers can create test scripts once and execute them across multiple platforms, ensuring consistent functionality and user experience.

Continuous Testing

In modern software development practices, continuous integration and delivery (CI/CD) pipelines are critical for rapid and frequent software releases. Low-code test automation seamlessly integrates with CI/CD workflows, enabling organizations to automate testing at each stage of the development process. This ensures early detection of defects, reduces the risk of regression issues, and facilitates faster feedback for developers.

Test Execution in the Cloud

Low code test automation tools offer the flexibility to execute tests in the cloud. This eliminates the need for dedicated test environments and reduces infrastructure costs. With cloud-based execution, organizations can quickly scale their testing efforts, accommodating the growing demands of complex low-code applications.

Conclusion

In conclusion, low-code test automation offers a powerful solution for streamlining software testing processes and accelerating time-to-market with enhanced quality.

By combining the flexibility of low-code development with the efficiency of test automation, organizations can improve test coverage, reduce manual effort, increase efficiency and productivity, accelerate software delivery, and foster collaboration between teams.

It is a strategic approach that empowers organizations to stay competitive, innovate faster, and deliver exceptional digital experiences to customers. By partnering with TestingXperts for low-code test automation services, businesses can drive success and achieve higher levels of software quality. To know more, contact our experts today.

Why Choose TestingXperts for Low-code Testing?

TestingXperts is a trusted partner with years of experience and expertise regarding low-code test automation services. Our comprehensive suite of test automation solutions is specifically designed to address the unique challenges of low-code applications. Here are the key differentiators that set us apart from our competitors:

Experience in Low-code Test Automation

TestingXperts has experience of delivering successful test automation solutions for low-code applications. With years of experience in the field, our testing professionals have deep domain expertise and hands-on experience in implementing test automation strategies tailored to low-code platforms. We understand the intricacies of low-code environments, enabling us to provide targeted and effective test automation services.

Specialized Test Automation Frameworks

We have developed test automation frameworks for low-code applications. These frameworks leverage cutting-edge technologies and best practices to streamline the test automation process, ensuring maximum coverage and efficiency. Our frameworks are continuously updated to keep pace with the evolving low-code landscape, enabling us to deliver high-quality test automation solutions effectively.

Accelerated Test Automation Delivery

At TestingXperts, we understand the importance of speed and efficiency in today’s fast-paced software development cycles. Our test automation methodologies and frameworks are optimized to deliver accelerated results. By leveraging automation tools and intelligent algorithms, we reduce the time and effort required for test automation script creation, execution, and maintenance. This enables you to achieve faster time-to-market while maintaining superior quality.

Comprehensive Test Automation Coverage

We emphasize comprehensive test automation coverage to ensure the thorough validation of your low-code applications. Our test automation services cover various dimensions, including functional testing, regression testing, integration testing, performance testing, security testing, and cross-platform testing. We help you identify and resolve issues early in the development cycle by addressing all critical testing aspects, ensuring robust and reliable low-code applications.

Seamless Integration with CI/CD Pipelines

Our experts understand the importance of seamless integration with continuous integration and continuous delivery (CI/CD) pipelines. Our test automation solutions seamlessly integrate with your existing development workflows, enabling continuous testing at each stage of the software development lifecycle. By automating the testing process, we ensure early detection of defects, faster feedback for developers, and reduced risk of regression issues, supporting your CI/CD initiatives.

The post A Comprehensive Guide to Getting Started with Low Code Test Automation first appeared on TestingXperts.

AI is increasingly being used to enable intelligent automation in low code development. AI-powered automation techniques can automate repetitive tasks such as code generation, testing, and quality assurance, freeing up developers to focus on more complex tasks. In addition, AI can analyze data and provide recommendations for optimal design and architecture decisions, making development more efficient and effective.

Natural language processing can also be used to translate natural language into code, making coding accessible to non-technical users. Predictive analytics can analyze large amounts of data to predict future trends and identify potential issues, allowing developers to proactively address them before they become problems. By leveraging AI to enable intelligent automation, low code development can increase productivity, reduce development time and costs, and deliver higher-quality applications.

Why Choose AI-driven low code development?

AI-driven low code development brings together two powerful technologies to help businesses develop software applications more quickly and efficiently than ever before. With low code development, non-technical users can create applications using visual interfaces and pre-built components, reducing the need for manual coding. By adding AI into the mix, these development platforms can automatically generate code and optimize application performance, further reducing the need for manual coding and testing.

The benefits of AI-driven low code development include:

Increased productivity and efficiency through automation and optimization

Automation and optimization are key strategies for businesses looking to increase productivity and efficiency. By automating repetitive or time-consuming tasks, businesses can free up their employees to focus on higher-level tasks that require creativity and problem-solving skills. This can improve productivity and job satisfaction while reducing the risk of burnout. Additionally, by optimizing workflows and processes, businesses can identify bottlenecks and inefficiencies and streamline their operations to reduce waste and increase output.

This can also lead to cost savings and improved customer satisfaction. With the rise of new technologies such as artificial intelligence and machine learning, businesses can now automate and optimize more complex tasks, such as data analysis and decision-making. By leveraging these technologies, businesses can gain insights and make decisions more quickly and accurately than ever before, further improving their productivity and efficiency. Automation and optimization are very powerful tools that can help businesses improve their operations, reduce costs, and stay competitive in today’s fast-paced business environment.

Enhanced accuracy and quality through intelligent decision-making

Intelligent decision-making can help businesses enhance accuracy and quality in their operations. By leveraging data and advanced analytics, businesses can gain insights into customer behavior, market trends, and operational performance. This can help them make more informed decisions and identify areas for improvement. Additionally, by using artificial intelligence and machine learning algorithms, businesses can automate decision-making processes, reducing the risk of human error and improving the accuracy of decisions. For example, in manufacturing, machine learning algorithms can be used to predict equipment failures before they occur, reducing downtime and improving product quality.

In healthcare, machine learning can be used to analyze medical images and assist in diagnosis, improving accuracy and reducing the risk of misdiagnosis. By making more accurate decisions, businesses can improve the quality of their products and services, reduce costs, and increase customer satisfaction. Furthermore, by continuously analyzing data and refining their decision-making processes, businesses can stay ahead of the competition and adapt to changing market conditions. Ultimately, intelligent decision-making can help businesses make better, more informed decisions, resulting in improved accuracy and quality in their operations.

Reduced development time and costs

AI low code development is a powerful approach that can help businesses reduce development time and costs. Traditional software development can be time-consuming and expensive, requiring significant resources to manually write and test code. With low code development, however, businesses can leverage pre-built components and visual interfaces to quickly and easily create applications, reducing the need for manual coding.

Additionally, by incorporating AI into the development process, these low code platforms can automatically generate code and optimize application performance, further reducing development time and costs. AI can also help identify potential bugs and errors before they occur, reducing the time and effort required for testing and debugging. By reducing development time and costs, businesses can bring products and services to market more quickly and at a lower cost, allowing them to stay ahead of the competition and respond to changing market demands.

Use cases of AI-driven low code development

AI-driven low code development has many use cases across various industries. Here are a few examples:

E-commerce:

AI-driven low code development can be used to create personalized shopping experiences for customers. By analyzing customer data, AI algorithms can generate personalized product recommendations and pricing, improving customer satisfaction and increasing sales.

Healthcare:

AI-driven low code development can be used to create applications for medical diagnosis and treatment. For example, AI/machine learning algorithms can be used to analyze medical images and assist in diagnosis, while low code development can be used to create user-friendly interfaces for healthcare professionals.

Manufacturing:

AI-driven low code development can be used to improve quality control and reduce downtime. For example, AI/machine learning algorithms can be used to predict equipment failures before they occur, while low code development can be used to create user-friendly interfaces for monitoring and maintenance.

Financial services:

AI-driven low code development can be used to create applications for fraud detection and prevention. By analyzing transaction data, AI algorithms can identify suspicious activity and alert financial institutions, reducing the risk of fraud.

Education:

AI-driven low code development can be used to create applications for personalized learning. By analyzing student data, AI algorithms can generate personalized learning paths and recommendations, improving student engagement and learning outcomes.

These are just a few examples of the many use cases for AI-driven low code development. Ultimately, this approach can be used in any industry where there is a need for efficient, user-friendly software applications that leverage the power of AI.

Companies that have successfully implemented AI-driven low code development

There are many companies that have successfully implemented AI-driven low code development to improve their operations and achieve business success. Here are a few examples:

Siemens:

Siemens, a multinational technology company, used AI-driven low code development to create an application that optimized the performance of wind turbines. The application used machine learning algorithms to predict turbine performance and maintenance needs, reducing downtime and improving overall turbine efficiency.

Uber:

Uber, a ride-hailing company, used AI-driven low code development to create an application that optimized the matching of riders and drivers. The application used machine learning algorithms to predict rider demand and driver availability, improving the efficiency and accuracy of the matching process.

Johnson & Johnson:

Johnson & Johnson, a healthcare company, used AI-driven low code development to create an application that improved patient care. The application used machine learning algorithms to analyze patient data and identify potential risks and opportunities for intervention, improving the quality and efficiency of patient care.

Examples of applications built using AI-driven low code development

There are many applications that have been built using AI-driven low code development. Here are a few examples:

Chatbots:

Chatbots are another popular application built using AI-driven low code development. These applications use natural language processing (NLP) and machine learning algorithms to understand and respond to customer inquiries, improving customer service and reducing the need for human intervention.

CRM software:

Customer relationship management (CRM) software is a popular application that has been built using AI-driven low code development. These applications use machine learning algorithms to analyze customer data and provide personalized recommendations for sales and marketing teams.

Predictive maintenance software:

Predictive maintenance software is another application built using AI-driven low code development. These applications use machine learning algorithms to analyze equipment data and predict potential equipment failures, allowing for proactive maintenance and reducing downtime.

Future trends of AI-driven low code development

AI-driven low code development is a rapidly evolving field, and there are several trends that are likely to shape its future. Here are a few:

Increased use of no-code and low-code platforms:

As the demand for software continues to grow, we can expect to see an increased use of no-code and low-code platforms, which allow users to build software without needing to know how to code. This trend will enable more people to create applications using AI-driven low code development, democratizing access to technology and empowering innovation.

Expansion of machine learning and natural language processing capabilities:

As machine learning and natural language processing continue to improve, we can expect to see more applications built using AI-driven low code development that leverage these capabilities. This will enable more sophisticated applications that can analyze complex data sets and interact with users more naturally.

Integration with the Internet of Things (IoT):

As the number of connected devices continues to grow, we can expect to see more applications built using AI-driven low code development that are designed to work with IoT devices. These applications will be able to collect and analyze data from a variety of sensors and devices, enabling more efficient and automated systems.

Emphasis on data privacy and security:

As the importance of data privacy and security continues to grow, we can expect to see more emphasis placed on building applications using AI-driven low code development that are secure and compliant with data privacy regulations.

Predictions on how AI will continue to impact low code development in the future

AI is likely to have a significant impact on low code development in the future. Here are a few predictions:

Increased automation:

As AI and machine learning algorithms become more sophisticated, we can expect to see increased automation of the software development process. This will enable low code developers to build applications more quickly and with fewer errors, allowing them to focus on more complex tasks.

Greater personalization:

AI will also enable low code developers to build applications that are more personalized to the needs of individual users. This could include recommendations for products and services, as well as tailored interfaces and user experiences.

Enhanced testing and quality assurance:

AI-driven testing and quality assurance tools will enable low code developers to identify bugs and issues in applications more quickly and accurately. This will help to reduce the time and resources required for testing and improve the overall quality of the software.

Increased collaboration:

As AI becomes more integrated into the software development process, we can expect to see increased collaboration between developers, data scientists, and other stakeholders. This will enable teams to work more efficiently and effectively, and to build applications that leverage the full power of AI and machine learning.

Conclusion

AI is likely to continue to play an increasingly important role in low code development in the coming years, enabling developers to build more sophisticated, personalized, and efficient applications with fewer resources and less time.

While still ensuring that they meet the needs of users and comply with data privacy and security regulations. As AI continues to evolve and become more sophisticated, we can expect to see even greater innovation in low-code development, with new applications and use cases emerging to meet the changing needs of businesses and consumers. Ultimately, AI-driven low code development will enable intelligent automation and transform the way we build and use software applications.

How TestingXperts can help with the testing of AI driven low code applications

TestingXperts is one of the world’s top 5 software testing and QA services company with extensive experience in testing AI-driven low code applications. TestingXperts offers a wide range of testing services, including automation testing, functional testing, performance testing, security testing, and more. For AI-driven low code applications, TestingXperts can help to automate the testing process, using tools and frameworks and beyond that its own accelerators like Tx-Automate, Capture and Tx-Hyperautomate to better the experience. TestingXperts also offers testing services for machine learning models used in AI-driven low code applications, including data preparation and model validation. With its deep expertise in software testing and its commitment to quality, TestingXperts can help to ensure that AI-driven low code applications are thoroughly tested, reliable, and deliver the expected value to end-users.

The post AI-Driven Low Code Development: A Booming Technology Trend first appeared on TestingXperts.

ChatGPT broke all internet records by reaching a million users in just 5 days of its launch. A conversational AI that can answer all-natural language-based questions, write codes, create social media posts, write long essays and do a lot of amazing things. The key aim of the platform in the UK and all over the world is to make the lives of mobile and web users easier. However, the question is how to use this amazing AI-based platform to help mobile and web app testers. And, most importantly, how can ChatGPT contribute to automated testing?

What is ChatGPT?

ChatGPT is a large language model developed by OpenAI. It’s a part of the GPT (Generative Pre-trained Transformer) family of models, specifically GPT-3.5 architecture, which is designed to generate human-like text based on a given prompt or input.

Its key purpose is to engage in conversations with users, answer their questions, and provide helpful information. The platform is trained on a massive amount of text from the internet, which allows the software to understand a wide range of topics and provide informative responses.

ChatGPT and Automated Testing

As an AI language model, ChatGPT is not directly involved in software development or automated testing in the United Kingdom (UK) and worldwide. However, as a language model that is designed to interact with humans, ChatGPT can be used to generate test cases and test data for automated testing systems.

In addition to this, ChatGPT can offer information and insights on testing best practices and techniques, as well as assist with documentation and communication within testing teams.

When we say ChatGPT test automation, it is about using ChatGPT to perform automated testing tasks such as regression testing, integration testing, and performance testing. For example, ChatGPT enables functional test automation to test the functionality of a web application by simulating user interactions and checking that the application responds correctly to various inputs.

But offering the codes that look accurate is just the start. ChatGPT and test automation go hand-in-hand. Ideally, ChatGPT is expected to provide the tests to generate. It would share all the details about the website version and generate perfect executable code that needs no changes. ChatGPT right now can’t do that but what it can do is still a lot though.

Let’s begin with a use case for ChatGPT for test automation, not to replace testing experts, but rather as a new low—coding method.

Can ChatGPT Generate Code for Use in Automated Testing?

As an AI language model, ChatGPT is capable of generating code for a variety of tasks.

Imagine you’re a software developer who just finished building a new feature for your application, and you want to ensure that it works as expected. Rather than manually testing the feature, you can use automated testing to automate the process and run tests repeatedly, catching any bugs or issues before they make it to production.

That’s where ChatGPT in test automation comes in. With its expertise in natural language processing and machine learning, it can generate test code that covers various scenarios and inputs, helping you ensure that your software is working as intended. Whether you need unit tests, integration tests, or end-to-end tests, it can generate code that fits your needs and specifications for ChatGPT software testing.

Below are a few possible use cases listed of ChatGPT in automated testing:

• Automating any test scenario

• Use CI/CD to build a complex test automation pipeline

• Use microservices for testing any application

• With detailed instructions for using the generated code, ChatGPT automation allows one to decode the code easily. Being a low-code tool, ChatGPT can also bring in code using the cucumber testing framework (on the basis of behavior-driven development of BDD).

Now, let’s dig more into ChatGPT and software testing.

Improving Software Testing with the use of ChatGPT

Here are some of the common QA activities that ChatGPT can perform:

As an AI language model, it can provide some suggestions on how you can potentially improve software testing:

Test Case Generation:

ChatGPT can help in generating test cases for your software based on the given specifications. By feeding the system with the requirements, it can generate test cases that ensure that the software meets those requirements.

Test Data Generation:

ChatGPT in automation testing can also help in generating test data for your software. By providing the system with the input parameters and their expected output, ChatGPT can generate the necessary data to test the software’s functionality.

Exploratory Testing:

ChatGPT can assist in performing exploratory testing, which is an unscripted and ad-hoc testing method. By leveraging its natural language processing capabilities, ChatGPT can help testers in exploring the software’s functionality and identifying any defects.

Test Automation:

By performing test automation with ChatGPT, it can help in automating the testing process. By leveraging its machine learning capabilities, it can learn from the manual testing activities and generate automated test scripts that can be used to test the software continuously.

Bug Prediction:

ChatGPT can also assist in predicting potential bugs in the software. By analyzing the code and the testing data, it can provide insights into the areas that are more likely to have defects, allowing testers to focus their efforts on those areas.

Using ChatGPT for Low code Testing

Low code testing involves testing applications built using low code development platforms that enable developers to build applications without writing a lot of code. These platforms often provide drag-and-drop interfaces, pre-built components, and other features that make it easier to build applications quickly.

Here are some ways ChatGPT can help with low code testing:

Test Case Generation:

ChatGPT can generate test cases automatically based on user requirements, specifications, and other inputs. It can analyze the low code application and provide test cases that cover all possible scenarios.

Test Data Generation:

ChatGPT can also help generate test data for low code applications. It can create test data based on different scenarios, such as positive and negative test cases, edge cases, and more.

Test Execution:

ChatGPT can execute test cases for low code applications and provide detailed reports on the results. It can identify issues, provide recommendations for fixing them, and ensure that the application meets the user’s requirements.

Code Analysis:

ChatGPT can analyze the code of low code applications and identify issues such as security vulnerabilities, performance issues, and more. It can provide recommendations for fixing these issues and ensure that the application is secure and performs well.

ChatGPT can be a valuable tool for low code testing, helping developers ensure that their applications are robust, reliable, and meet the user’s requirements.

Downsides of ChatGPT for Automated Testing

In a very limited time, ChatGPT has shown a lot of promises in the case of low-code tools for automated testing.

Regardless of its benefits, ChatGPT for software testing has its share of limitations, which include the following:

• The platform does not implement the application code being tested itself. ChatGPT testing tool thus cannot decide if the generated code is achievable.

• ChatGPT cannot identify the despised methods – nor does it have an effective way to correct the issue.

• ChatGPT usually uses common page structures in its generated code. The users, therefore, need to pick out the issue to request an updated code version.

Despite these limitations, ChatGPT has very good potential as a low-code solution for automated testing. However, it is required that QA testers use this AI model after completely understanding the programming language used and the application under test.

Can ChatGPT assist in Test Automation?

ChatGPT can help with test automation. As a language model, it can provide guidance and suggestions on test automation strategies, tools, and best practices.

Here is how ChatGPT can help with test automation:

Test Automation Planning:

ChatGPT can assist with test automation planning by providing recommendations on which tests are best suited for automation, identifying potential test automation frameworks, and suggesting how to integrate automation into the development process.

Test Automation Tools:

ChatGPT can help in selecting the right test automation tools based on the project’s requirements, providing a comparison between different tools, and offering advice on how to evaluate tools effectively.

Test Automation Frameworks:

ChatGPT can suggest popular test automation frameworks and advise on the best framework to use for a particular project.

Test Automation Best Practices:

ChatGPT can help with providing best practices for test automation, such as creating maintainable test scripts, managing test data, and dealing with flaky tests.

Troubleshooting:

ChatGPT can help in identifying and troubleshooting issues with test automation scripts, such as debugging failing tests or identifying bottlenecks in the test execution.

Will ChatGPT Replace Testing Teams?

As a code generation tool, ChatGPT is comparatively the most powerful tool for generating natural language. Since it is new to the market, ChatGPT algorithm may take some time to mature fully. This cannot be trusted completely for performing automation testing. In addition to this, written test cases from ChatGPT cannot be taken as 100% right.

To sum this up, ChatGPT for automation testing is a good idea, however, it is not mature enough to replace AI-based test automation.

How is TestingXperts offering AI and Automation Testing Services in the UK?

ChatGPT QA can be the next big thing, as low-code testing is becoming an effective aspect of testing that needs to be included in every product team’s plan. It makes space for less technical users to get more embroiled with the software delivery lifecycle, permitting a culture of quality to be unlocked across the organization. Since there is a lot of value from other forms of testing like unit and integration testing, it can be limited by the number of trained engineers on hand and time required to complete end-to-end testing.

The post ChatGPT and its Contribution in Test Automation first appeared on TestingXperts.

Content

1. What is Cucumber Testing?
2. How is Cucumber Testing Different from Traditional forms of Testing?
3. Benefits of Cucumber Testing
4. Why is Cucumber Testing Gaining Popularity Among Digital Businesses?
5. Conclusion
6. How TestingXperts Helps Businesses with Cucumber Testing?

What is Cucumber Testing?

Cucumber is a testing framework that allows developers to write and run automated tests using natural language syntax. It follows the BDD (Behavior-Driven Development) approach, which emphasizes collaboration between developers, QA, and non-technical stakeholders to define and validate software requirements. Cucumber tests are written in feature files, which describe the desired behavior of a software application using Gherkin syntax. These feature files are then parsed by Cucumber and executed against the application code. Cucumber testing helps improve the quality and reliability of software by providing a common language for developers and stakeholders to communicate requirements and ensure they are met.

How is Cucumber Testing Different from Traditional forms of Testing?

Cucumber testing is a form of behavior-driven development (BDD) testing that focuses on defining and testing the behavior of an application from a user’s perspective. Traditional forms of testing, on the other hand, typically focus on testing the functionality of an application based on its technical specifications.

Here are some key differences between Cucumber testing and traditional forms of testing:

Language:

Cucumber testing uses a simple, human-readable language called Gherkin to describe the expected behavior of an application. This makes it easier for non-technical stakeholders to understand and contribute to the testing process. Traditional forms of testing typically use programming languages such as Java, Python, or Ruby.

Focus:

Cucumber testing focuses on testing the behavior of an application from a user’s perspective. This means that scenarios are defined based on the actions that a user might take when interacting with the application. Traditional forms of testing focus on testing specific functionality of an application, such as individual methods or functions.

Collaboration:

Cucumber testing encourages collaboration between developers, testers, and business stakeholders. By defining scenarios in a language that is easy to understand, everyone can contribute to the testing process. Traditional forms of testing may be more siloed, with developers writing code and testers writing test cases separately.

Automation:

Cucumber testing can be automated using tools like Selenium or Appium. This makes it possible to run tests quickly and frequently, providing rapid feedback on changes to the application. Traditional forms of testing may be more manual, requiring testers to manually execute test cases.

Overall, Cucumber testing is a collaborative, user-focused approach to testing that encourages frequent feedback and automation. While it may require some initial setup and training, it can be a powerful tool for ensuring the quality and behavior of your application.

Benefits of Cucumber Testing

Improved Quality:

Helps improve the quality of software by identifying bugs and issues early in the development process, reducing the likelihood of defects in the final product.

Increased Collaboration:

Encourages collaboration between developers, testers, and business stakeholders by providing a common language and framework for discussing requirements and testing scenarios.

Automated Testing:

Cucumber testing can be automated, reducing the time and effort required for manual testing and enabling frequent testing throughout the development process.

Faster Feedback:

Provides quick and clear feedback on the status of test cases and helps identify the root cause of failures, allowing developers to fix issues quickly.

Reusability:

Allows the creation of reusable test cases, which can be used across different projects and applications. This reduces the effort required for testing and ensures consistent quality across projects.

Maintainability:

Allows the separation of test cases from the underlying code, making it easier to maintain tests as the application evolves. This reduces the risk of test cases becoming obsolete and helps ensure the continued quality of the software.

Cost-Effective:

Cucumber testing is a cost-effective way to ensure software quality, as it can identify issues early in the development process, reducing the cost of fixing defects later on.

Why is Cucumber Testing Gaining Popularity Among Digital Businesses?

Cucumber testing is gaining popularity among digital businesses because it offers a unique approach to software testing that prioritizes collaboration between technical and non-technical stakeholders. Cucumber is a tool that uses plain text and Gherkin syntax to describe test scenarios in a way that can be easily understood by both developers and non-technical stakeholders. This approach promotes communication and collaboration, which can lead to better software quality and faster time-to-market. Additionally, Cucumber testing can be used for both functional and non-functional testing, making it a versatile tool for ensuring the overall quality of digital products.

Another reason for the growing popularity of Cucumber testing is its ability to automate testing processes. Cucumber allows for the creation of automated acceptance tests, which can be run as part of a continuous integration and delivery (CI/CD) pipeline. This enables teams to catch bugs earlier in the development process, reducing the risk of costly errors and downtime in production. Automation also saves time and resources, allowing teams to focus on developing new features and improving the user experience.

Finally, Cucumber testing is gaining popularity among digital businesses because it supports agile development methodologies. Agile emphasizes iterative development and continuous feedback, which aligns well with the collaborative and flexible approach of Cucumber testing. By incorporating Cucumber into their testing processes, teams can easily adapt to changes in requirements and feedback from stakeholders, ensuring that the end product meets the needs of the business and its users. Overall, Cucumber testing offers a powerful set of tools and techniques that can help digital businesses improve their software quality, speed up their development processes, and stay competitive in a rapidly evolving market.

Conclusion

Cucumber testing is a powerful tool for automating software testing and ensuring the quality of your code. It allows for collaboration between developers, testers, and other stakeholders in the software development process, and promotes a clear understanding of the expected behavior of a system. Cucumber’s user-friendly syntax and ability to generate readable reports make it an ideal choice for teams looking to implement behavior-driven development. By leveraging the power of cucumber testing, teams can streamline their testing process, catch defects early, and ultimately deliver better software products to their users.

How TestingXperts Helps Businesses with Cucumber Testing?

TestingXperts (Tx) is one of the 5 largest pure-play software testing services providers globally. Tx has been chosen as a trusted QA partner by Fortune clients and ensures superior testing outcomes for its global clientele. We have rich expertise in enabling end-to-end testing services for global clients across various industry domains like healthcare, telecom, BFSI, retail & eCommerce, etc.

We provide comprehensive testing services using Cucumber, an open-source testing tool that allows for Behavior Driven Development (BDD) and facilitates collaboration between technical and non-technical team members. Our team of experienced testers can assist with everything from writing feature files to executing and analyzing test results.

Our Cucumber Testing Services Include:

Test Strategy Development:

Our testing experts work with you to understand your business needs and create a customized testing strategy for your application. We ensure that the strategy aligns with your goals and objectives and meets the specific needs of your organization.

Test Planning and Execution:

We help you create detailed test plans and test cases based on your requirements. Our team can execute the tests and provide you with accurate and detailed test results. We also offer automated testing services to help you achieve faster testing and quicker feedback loops.

Test Maintenance:

Our team ensures that your tests are up-to-date and continue to deliver valuable insights. We perform regular maintenance activities such as updating test cases, fixing broken tests, and ensuring that tests are running efficiently.

Integration Testing:

We can help you test the integration of your application with other systems or third-party services. Our team is experienced in testing API integrations, database integrations, and other types of integrations.

Performance Testing:

Our team can assist with performance testing to ensure that your application can handle expected levels of traffic and load. We can help you identify and fix performance bottlenecks before they impact your users.

Security Testing:

We can help you identify potential security vulnerabilities in your application by performing security testing. Our team can help you identify vulnerabilities such as injection attacks, cross-site scripting (XSS), and other types of security flaws.

Test data management strategy:

Our team can help you devise a robust test data management strategy that enables a robust automation framework and more flexible scripts.

The post Cucumber Testing The Secret Weapon for Effective Software Testing first appeared on TestingXperts.

Content 1. Cypress Web Automation: An Overview 2. Why is Cypress Automation Trending in the QA Industry? 3. Seven Key Benefits of Cypress Automation for DevOps-driven Businesses 4. Best Practices of Cypress Automation 5. Conclusion 6. How TestingXperts Helps Businesses with Cypress Automation

Cypress Web Automation: An Overview

Cypress is an open-source testing tool that facilitates automated testing of web applications. It offers a modern and robust approach to web automation, making it easy to write and maintain tests. Cypress offers several features that make it stand out from other testing tools, such as its ability to run tests in real-time, its ability to debug tests easily, and its ability to automatically wait for page elements to load before executing commands.

Cypress has a powerful command-line interface, and it integrates seamlessly with popular development frameworks like React and Angular. Overall, Cypress is an excellent tool for automating web testing, offering developers and testers a reliable and efficient way to ensure their applications are performing as expected.

Why is Cypress Automation Trending in the QA Industry?

Cypress automation has become increasingly popular in the QA industry due to its unique features and capabilities. Cypress offers a powerful and intuitive testing framework that allows QA engineers to write automated tests quickly and efficiently. It offers a modern approach to testing web applications that integrates seamlessly with modern front-end frameworks such as React, Angular, and Vue. Its test runner offers a visual representation of the test runs, which makes it easy for testers to identify and troubleshoot issues. Cypress also provides built-in debugging tools, which makes it easier to diagnose and fix issues quickly.

Cypress provides a unique advantage over other automation tools in terms of speed and stability. Its architecture is designed to run tests in the same environment as the application, eliminating the need for a separate browser or driver. This enables faster test runs, as well as more stable tests that are less prone to flakiness. Cypress also offers real-time reloading, which means that changes made to the application code are immediately reflected in the test, making it easier to develop and debug tests.

As a result, many companies are turning to Cypress automation as a reliable and efficient tool for their testing needs, helping them save time and resources while delivering high-quality software.

Seven Key Benefits of Cypress Automation for DevOps-driven Businesses

Speed and reliability:

Cypress is known for its high speed and reliability, which is critical for continuous integration and deployment. Cypress runs tests in the browser and provides instant feedback, making it faster than other testing tools.

Easy to use:

Cypress has a user-friendly interface and a simple API that allows even novice developers and testers to write tests. It also provides excellent documentation, making it easy to get started.

Cross-browser testing:

Cypress allows developers and testers to test their web applications across multiple browsers, including Chrome, Firefox, and Edge, ensuring that the application works on all platforms.

Real-time debugging:

Cypress provides real-time debugging capabilities that allow easy identification of bugs along with quicker This feature makes it easy to pinpoint the root cause of a problem.

Continuous integration and deployment:

Cypress is well-suited for DevOps-driven businesses because it integrates seamlessly with popular CI/CD tools such as Jenkins, CircleCI, and Travis CI.

Open source:

Cypress is an open-source tool, which means that businesses can use it for free and even contribute to its development.

Community support:

Cypress has a large and active community of developers who share tips, best practices, and solutions to common issues. This community support makes it easy to get help and learn from other developers.

Best Practices of Cypress Automation

Here are some best practices to follow while using Cypress automation:

Organize tests with a clear folder structure:

Organize the tests in a clear folder structure based on functionality, feature, or user stories, and keep the test files in a single folder to avoid confusion.

Write descriptive test names:

Write test names that are descriptive and easy to understand. Test names should be specific and accurately describe the test being performed.

Keep tests short and focused:

Keep each test short and focused on testing a specific feature or functionality. This will make it easier to identify the cause of a test failure.

Use custom commands:

Use custom commands to simplify repetitive tasks, such as logging in or navigating to a certain page, and to make the test code more readable.

Use fixtures:

Use fixtures to load data into the tests. This helps ensure that the tests run consistently and that they cover a wide range of scenarios.

Use the Page Object Model:

Use the Page Object Model design pattern to separate the tests from the implementation details of the application. This helps make the tests more maintainable and easier to read.

Use beforeEach() and afterEach() hooks:

Use the beforeEach() and afterEach() hooks to perform setup and cleanup tasks before and after each test. This helps keep the tests isolated and reduces the risk of false positives.

Use assertions wisely:

Use assertions to validate that the application behaves correctly. Avoid using too many assertions in a single test, as this can make it difficult to identify the cause of a test failure.

Use Cypress Dashboard:

Use the Cypress Dashboard to store and view test results. This can help quickly identify and fix test failures, as well as track overall test coverage.

Use continuous integration:

Use continuous integration (CI) to automate the testing process. This can help ensure that the tests are always running, and that any issues are caught early in the development cycle.

Conclusion

Cypress automation offers numerous benefits for modern software development. Its intuitive and user-friendly interface makes it easy to learn and use, while its powerful testing capabilities provide developers with a reliable way to ensure that their applications function as intended.

Cypress automation saves time and resources by automating repetitive tasks, allowing developers to focus on more important aspects of their work. Additionally, the ability to run tests continuously in the background helps catch bugs early on in the development cycle, leading to faster and more efficient development. With all of these benefits and more, it’s no wonder that Cypress automation has become such a popular tool among developers.

How TestingXperts Helps Businesses with Cypress Automation

TestingXperts (Tx) is one of the Top 5 pure-play software testing services providers globally. Tx has been chosen as a trusted QA partner by Fortune clients and ensures superior testing outcomes for its global clientele. We have rich expertise in enabling end-to-end testing services for global clients across various industry domains like healthcare, telecom, BFSI, retail & eCommerce, etc.

We specialize in providing best-in-class Cypress automation services that are tailored to meet the specific needs of our clients. Our team of experts has extensive experience in using the Cypress framework to develop automation scripts that help streamline the testing process, reduce the overall testing time, and improve testing efficiency.

Key Benefits of Our Cypress Automation Services:

Faster testing outcomes:

Our Cypress automation services can help businesses significantly reduce the testing time by automating repetitive testing tasks.

Improved testing accuracy:

Automation ensures that tests are performed consistently and accurately, reducing the likelihood of human error.

Enhanced testing coverage:

Automation allows you to test a wider range of scenarios than manual testing, ensuring that your application is thoroughly tested.

Cost savings:

By reducing the time and effort required for testing, our Cypress automation services can help you save money in the long run.

Our Cypress automation services process is designed to ensure that we deliver the best possible results to our clients.

Here are the key steps involved in our process:

Understanding your testing requirements:

We work closely with you to understand your testing requirements and identify the areas of your application that need to be tested.

Developing the automation framework:

Our team of experts develops a customized automation framework using Cypress that is tailored to your specific needs.

Creating automation scripts:

We create automation scripts that simulate real-world user actions and interactions with your application, ensuring that it is thoroughly tested.

Executing the tests:

We execute the automation scripts and analyze the results to identify any issues or bugs that need to be addressed.

Reporting and documentation:

We provide detailed reports and documentation that outline the results of the testing process, including any issues or bugs that were identified.

The post Cypress Automation: 7 Key Benefits to DevOps-driven Businesses first appeared on TestingXperts.

Automated data testing helps accelerate the software delivery lifecycle by providing rich, compliant and error-free data. This infographic reveal the 4 major benefits of automated data testing and how it impacts digital businesses.

The post 4 Benefits For Businesses with Automated Data Testing first appeared on TestingXperts.

Content 1. An overview of codeless test automation 2. Difference between low-code and codeless test automation 3. Why do digital enterprises need codeless test automation in 2023 and beyond? 4. How Does Codeless Test Automation Works? 5. Top codeless test automation tools in 2023 6. Conclusion 7. How Tx Can Help You with Your Low-code, Codeless test automation needs

An overview of codeless test automation

The codeless automation trend has gained immense traction in the global digital system. The codeless automation platforms are software programs requiring little to no coding knowledge. Codeless test automation processes enable predesigned templates for workflows with a drag-and-drop interface for simplified customization. This helps business executives with no back-end computer programming knowledge to manage the workflows without any dependency. Codeless test automation platforms are gaining much attention due to the wide range of benefits they offer to digital businesses, such as quicker product releases, process scalability, self-service capability, and so on.

According to GlobeNewswire, the global codeless development platform market is predicted to generate a revenue of $187.0 billion by 2030, rising from $10.3 billion in 2019. The global market is expected to grow at a CAGR of 31.1% during the forecast period 2020-2030.

Difference between low-code and codeless test automation

Criteria	Low code automation	Codeless test automation
Coding Knowledge	Low code is created for Dev teams and needs little coding knowledge. The platform offers a means of automating things faster, but only for people with tangible coding skills	Codeless is designed especially for business executives, and no coding knowledge is needed
Automation Process	Low code still relies on some coding for designing automated processes	Codeless platforms allow the end-user to dictate the automation process design through simple drag-and-drop manipulation
Dependency on Dev	Low code allows users to handle automation up to a certain point. So, the Dev team or tech-savvy will have to take charge and drive QA automation	Codeless platforms are simplified and give absolute independence to the user since they don’t need any technical knowledge to operate the platform
Ease of Customization	It can be completely customized	Only pre-built templates can be used

Why do digital enterprises need codeless test automation in 2023 and beyond?

Leverage AI and ML:

Codeless automation testing tools integrate AI or ML. The adoption of AI and ML is staggeringly high because these latest technologies combine human intelligence and computer intelligence to accelerate development, reduce errors, and automatically handle processes.

Ensure time-saving:

One of the primary advantages of codeless automation testing is time-saving. As testers don’t have to spend their time coding or learning to code — it is possible to start with codeless testing from day one.

Enable simplified test automation:

When test automation is created through visual UI workflows, the entire code is generated at one place, making QA automation easy to understand and perform. QA teams can automate cases as soon as the app UI is completed.

Ensure higher efficiency:

Codeless test automation enables faster feedback cycles and faster time to market as it reduces software development time. Since tests are executed rapidly in a highly controlled environment, codeless test automation enables higher efficiency.

Enhances speed of app delivery:

One of the best advantages of moving to codeless automation testing is the speed with which DevOps teams manage the app development. Codeless automation testing offers a simplified UI that enables quick learning. Since DevOps teams need not write any code, QA teams can create test cases aided by AI, therefore enhancing both performance and the speed of testing.

Ensures low product maintenance and high scalability:

Codeless test automation makes it possible to automate tests with visual UI workflows which inherently adhere to the current business rules and best practices, hence making the application testing highly scalable and low maintenance

Enables minimal resource allocation:

When testers are not required to spend their time automating their regression tests by creating test cases, they have more time for exploratory application testing. With codeless test automation, there’s no need to involve developers in the creation of UI tests, which is cost-effective.

Reduces regression testing efforts:

Regression testing is time-consuming, and it’s best to automate it. Regression testing being monotonous and repetitive, codeless test automation enables QA engineers to significantly decrease their efforts and focus on other important critical aspects of testing, such as exploratory or acceptance testing.

Ensures seamless CI/CD integrations:

Codeless automation testing tools are significantly advantageous for teams with agile and DevOps cultures. Seamless CI/CD integration ensures all the application updates are done regularly.

How Does Codeless Test Automation Works?

Step 1: Choose the Right Tool

Select an automation tool that suits project needs. It should support the platforms to be tested, provide integration capabilities with existing systems, and be user-friendly.

Step 2: Understand the Application

Before beginning the testing process, thoroughly understand the software application that will undergo testing. This includes familiarizing with its functions, features, and possible user interactions.

Step 3: Identify & Record Test Cases

Identify key test cases that need to be automated. These usually include high-risk areas, repeated test cases, large data sets, and functionalities that have frequent regression errors. Start the ‘Record’ feature with the selected tool and manually perform the test case steps on the software application. Execute each step precisely, as the tool will capture every interaction.

Step 4: Review and Save the Test Script

Once you finish recording, the tool will automatically create a script. Review this script for accuracy and make any necessary adjustments. Then, save this script for future use.

Step 5: Playback the Test

Utilize the ‘Playback’ feature to run the test. The tool will replicate earlier actions exactly, performing the test automatically.

Step 6: Analyze the Results

After completing the test, the tool will generate a detailed report. Review this report to analyze the test results and identify any issues or bugs.

Step 7: Debug and Maintain

The QA engineer can easily update the test script if there are any test issues or application changes. The visual modelling feature of codeless tools makes debugging and maintenance easier.

Step 8: Integrate and Schedule

Integrate the codeless testing tool with your CI/CD pipeline and ALM tools for seamless operations. Schedule tests as needed to ensure consistent quality assurance.

Top codeless test automation tools in 2023

The following are the key areas to look for when choosing the codeless test automation tools in 2023:

• Allows running of the most time-consuming and repetitive QA tasks without any coding knowledge, such as smoke tests and regression tests

• An easy-to-use UI that is straightforward to maintain a test suite with frequent product updates

• Enables testing on multiple OS and browsers

• A scalable tool that adapts to the evolving size and maturity of the team

• A comprehensive solution that enables quick testing with a few clicks

Based on the above criteria, here is the list of recommended codeless test automation tools:

Conclusion

Codeless test automation does a great job of enabling business executives to manage automated tests without the knowledge of coding skills. With ongoing technological progress, codeless test automation is evolving steadily. Given the noteworthy benefits mentioned above, we can say that codeless test automation makes application testing straightforward and efficient. Hence, digital businesses should leverage codeless test automation from a professional QA services provider and embed these techniques in their agile workflows to achieve better product development.

How Tx Can Help You with Your Low-code, Codeless test automation needs

• Tx has partnered with Sofy, the leading AI-based codeless quality automation platform.

• Leverage the combination of advanced technologies like AI, ML, RPA, BPM, etc.

• Ensure process and operational efficiency, save time & cost and deliver a great CX

• Profound knowledge and ability to perform scriptless test automation

• Substantial reduction in test design and QA maintenance efforts

The post The Need for Codeless Test Automation for Digital Enterprises in 2023 and Beyond first appeared on TestingXperts.