A change in your code or program can have an adverse effect on your existing functionality. The basic functionality should always be verified whenever you make code changes.
Regression testing is a type of testing which ensures that any change in the application code does not affect the old working code and its features. In software development, any change to the code with respect to enhancements, bug fixes, or new functionality might accidentally lead to new errors or the recurrence of old defects. So, it is always important to ensure that the application is working fine even after the changes. Hence, regression testing is highly essential when there is a continuous change in the application. Any software after changes should undergo regression testing. If not, the application might fail in the live environment.
At QAonCloud, we do regression testing for each code change or functionality change. We create regression test suites based on the business requirements, priority modules, important features, etc and execute them during every test cycle and ensure that the system is working as expected. We prioritize the test cases for the regression test suite based on the functionalities that are more important, functionalities that fail frequently, complex test cases, test cases that cover the recent code changes, etc.
Regression testing requires the execution of a set of test cases for every test cycle, which is a time consuming and tedious process. So, QAonCloud focuses on automating the regression testing efforts that would save time and costs.
We understand your priorities, list out the basic functionality cases, and automate the regression suite using opensource tools. We run a full regression suite to ensure complete functionality coverage after any server patches, code changes, and database upgrades of your code.
- We ensure that the addition of new code to your software does not affect the existing features by re-executing the full or partial selection of test cases.
- Manual/Automated scripts ensure all the existing functionalities are working fine.
- The Regression test suite is selected based on the frequently used functionalities, critical features, and also based on the business impact.
- We may also suggest automating the previously executed test cases, thereby saving time and money.
- Our team maintains and sends you the report for each regression cycle.
Choosing QAonCloud as Software Testing Partner"With QAonCloud, Startups and SMEs can get all types of testing services at a lower cost. The brochure below gives you an idea of what we offer and how we can help. From manual testing to automated testing, we've got you covered"
The Flexibility of QA Partnerships: A Game-Changer for Business Expansion?"The business world is always changing and expanding. With this in mind, businesses need new and innovative ways to approach quality assurance (QA). QA partnerships have emerged as a game-changer for businesses looking to expand. The QA partner offers flexibility in their approach to quality control and ensuring that the products meet the highest standards. Let's explore how businesses can expand cost-effectively and efficiently by leveraging the flexibility of QA partnerships. QA Partnerships: The Way Forward for Business Expansion The increasing demand for software testing and quality assurance services from businesses in various sectors, including healthcare, retail, and finance, is driving this growth. In order to achieve growth, it is crucial for businesses to maintain the highest possible standards for their products, and enlisting the help of a QA service provider can make a significant difference. Flexibility in QA: An Agile Approach to Quality Assurance The flexibility offered by QA partnerships is a significant advantage for businesses. According to a report by Deloitte, agile methodologies can help businesses achieve up to 75% faster time-to-market, reduce development costs by up to 25%, and achieve up to 80% better quality products. With a QA partnership, businesses can adopt an agile approach to quality assurance, allowing them to adapt to market and customer demands quickly. This ensures that products and services are delivered on time, with high-quality standards that meet customers' needs. Cost-Effective QA Solutions: Reducing Overheads for Startups According to a report by Statista, the failure rate of startups in the US is around 90%. One of the primary reasons for this is the inability of startups to manage their finances effectively. By partnering with QA services, startups can benefit from the expertise of experienced professionals without having to incur the overhead costs associated with an in-house team. This allows startups to keep costs under control while ensuring that their products or services meet the required standards. QA Partnerships for Fast-Growing Businesses: Scaling Up with Ease As businesses grow, the demands on their QA processes can increase exponentially. According to a report by Gartner, 80% of software development projects experience delays due to poor software testing and quality assurance. By partnering with QA services, businesses can scale up their operations quickly and efficiently, ensuring that their products or services meet the required standards while controlling costs. QA Partnerships for Startups Startups face unique challenges in today's fast-paced business world, and one of the biggest challenges is building a reliable, talented team while keeping costs low. By partnering with a QA team, startups can upscale or downgrade their teams at a fraction of what they spend on in-house teams. QA partnerships can help startups to maintain the flexibility to adjust the size of their team as needed. Flexible QA Teams QA partnerships can help startups to maintain the flexibility to adjust the size of their team as needed. These partnerships can provide access to a pool of talented QA professionals, which can be scaled up or down to match the business's needs. A QA partnership enables startups to tap into resources that can provide them with a wide range of skill sets, including testing and automation, without the added cost of hiring full-time employees. Business Agility Startups need to be agile to keep up with the changes in the market. And QA partnerships help them to maintain agility. When the demand increases, startups can upscale by adding more QA testers, automation engineers, or developers. On the other hand, if there's a slow season, startups can downscale their team and only pay for the services they need. Scalability Moreover, QA partnerships can play a vital role in successful business expansion. When businesses plan to expand their operations, they must ensure their product quality. QA partnerships can help businesses to achieve this goal by providing access to a team of experienced testers. The team should be able to evaluate the quality of their product or service. Staying Market Ready QA partnerships can also help businesses ensure their product is ready for the market. A QA team can evaluate the product's usability, performance, security, and compatibility with different devices, browsers, and operating systems. This ensures that the product meets the market's standards and can be easily adopted by the customers. Final Thoughts QA partnerships can provide businesses flexibility, cost-effective solutions, and scalability during expansion. End-to-end QA services can provide agile and customized testing solutions to meet the specific needs of businesses looking to expand. QAonCloud's experienced professionals can offer various QA services, including functional, performance, security, and usability testing. The team ensures that the products or services meet the highest quality and performance standards."
How AI-driven Testing is Changing QA Test Automation"How AI-driven Testing is Changing QA Test Automation As technology evolves, so do the testing processes. Artificial intelligence (AI) is making its way into the quality assurance (QA) world, revolutionizing how organizations approach software testing and automation. AI testing has become an invaluable tool for many companies, offering streamlined test automation and improved QA processes. According to Gartner, nearly 50% of software testing efforts will be automated through AI by 2020. AI-driven testing transforms how companies create and execute software tests, providing faster and more efficient methods of catching defects. By leveraging AI technologies, QA teams can automate many manual tasks associated with software testing. This allows testers to identify potential issues in a fraction of the time it would take to test each feature manually. Additionally, it can be used to create more comprehensive tests that better simulate real-world user interaction. What is AI-driven testing, and how does it work? It is an approach to software testing that uses AI and machine learning technologies to automate the process of creating and executing tests. It combines traditional test automation with artificial intelligence capabilities such as natural language processing (NLP), image recognition, and predictive analytics to speed up the process of writing automated tests. Using this, testers can define and execute tests without writing code manually. AI-driven testing tools can generate test scenarios based on usage patterns, allowing testers to identify software defects quickly. Additionally, these tools can detect changes in user behavior and automatically update tests accordingly. How does AI-driven testing improve the quality of software products and applications? It has become essential for software quality assurance teams, offering many benefits over traditional manual testing. By leveraging AI technologies, testers can create comprehensive test suites that better simulate real-world user behavior and identify potential defects in the code. Furthermore, automated tests combined with AI are faster and more efficient than manual tests, allowing organizations to save time and resources. Here are 5 key benefits: 1. Improved Accuracy With AI-driven testing, testers can create more comprehensive test scenarios that better simulate real-world user behavior and accurately identify potential defects in the code. By leveraging predictive analytics, these tests can also detect changes in usage patterns and automatically update tests accordingly. This greatly improves the accuracy of test results and helps teams quickly identify and fix software issues before they become major problems. 2. Faster Test Execution The tools are designed to automate many manual tasks associated with software testing, including test case creation, execution, and analysis. This allows testers to create comprehensive test scenarios in a fraction of the time it would take to test each feature manually. Additionally, these tools can be used to execute tests faster and more efficiently than manual tests, reducing testing time and allowing organizations to deploy new features or releases quickly. 3. Reduced Costs It reduces the cost of software development and maintenance by eliminating manual test creation and execution. By automating many of the tasks associated with testing, organizations can save time and resources that would have otherwise been spent on hiring manual testers or writing long test scripts. Additionally, these tools allow teams to quickly identify potential defects in their code, reducing the amount of time spent on debugging and improving overall quality assurance. 4. Improved User Experience These tools can identify potential user experience (UX) design issues. By simulating real-world user interactions, these tests can detect usability issues that would have otherwise gone undetected. This helps teams quickly identify and fix problems before they impact the user experience, ensuring customers have a positive experience when using their products. 5. Increased Productivity With the help of AI, automating many of the manual tasks associated with software testing helps focus on more complex tasks that require human input. This allows teams to quickly create comprehensive test scenarios that can accurately identify potential defects in the code. These tools can also be used to generate reports and insights into user behavior, helping teams gain valuable insight into their products and make informed decisions about future releases. How can your organization start using AI-driven testing for QA test automation? It can help organizations improve the quality of their software products and deliver better user experiences. To get started: 1. Identify your testing needs Start by understanding exactly what type of tests you need. Take a look at your current test suite and identify the types of features and scenarios that could benefit from automated testing. 2. Choose a Testing Platform Once you understand your needs, research different platforms and select one that meets your requirements. Consider features such as ease of use, support for different test frameworks, and pricing. 3. Establish testing processes Set up a consistent testing process using the AI-driven platform to ensure accurate results. This should include steps such as defining test cases, creating automated tests, running tests, and analyzing results. 4. Monitor progress Use the insights generated to monitor product performance, identify issues quickly, and take corrective measures when necessary. This will help ensure that your products deliver a positive user experience across different platforms. 5. Make improvements Constantly update tests as needed to keep up with changes in user behavior or product features. This will help ensure that your tests are up to date and reflect current usage patterns, helping you stay a step ahead of the competition. Conclusion By using AI-driven testing tools, organizations can make their QA test automation processes more efficient, save time and resources, deliver better user experiences, and improve the quality of their software products. QAonCloud provides a comprehensive testing platform that can help teams quickly create reliable tests and gain valuable insights into user behavior. Contact us today to learn more about our services and how we can help you achieve your goals."
QA Testing for Tech Startups – Finding The Right Balance Between Speed and Quality"The pace of innovation in the tech industry is rapid, and startups must work quickly to stay ahead of the competition. But regarding product QA for tech startups, speed can sometimes come at a cost. Finding the right balance between speed and quality is essential for any tech startup looking to succeed in today's dynamic market. When running a tech startup, one of the most important decisions you'll need to make is how much time and effort to devote to Quality Assurance. On the one hand, it's essential for every product or service your startup offers to be reliable and secure; on the other hand, increasing QA efforts can slow down development cycles and take resources away from other areas of your business. So how do you find the right balance between speed and quality? In this blog, we'll explore strategies that tech startups can use when dealing with QA issues so that they can focus on building great products while still ensuring high standards of customer satisfaction. Why is Speed Important in QA for Tech Startups? Speed is essential for QA for tech startups, as the industry constantly evolves and new products are being released rapidly. As a startup, keeping up with these changes can be difficult if you don't have a streamlined and efficient QA process in place. Additionally, agile development processes require quick feedback cycles to identify and address problems quickly. Avoiding the need for expensive bug-fixing efforts after your product release can help reduce costs Strategies for Finding the Right Balance The best way for tech startups to ensure speed and quality is to incorporate a comprehensive QA process into their product development cycles. This process should start as early as possible in the cycle and remain flexible to accommodate changes. Here are some strategies that tech startups can use to find the right balance between speed and quality: Automate Wherever Possible Automation is one of the most effective strategies for ensuring that a tech startup’s QA process remains efficient while still delivering the desired quality standards. Automating tasks like regression testing and smoke tests can help reduce human error and save time, allowing you to focus on more complex areas of your product. Additionally, automated tests can run continuously in the background, helping minimize development cycles and identify issues before they become critical. Invest in Quality Testing Tools Another key strategy for achieving speed and quality with your QA process is investing in quality testing tools tailored to tech startups. Many different types of tools are available, ranging from basic manual testing tools to more advanced automation solutions. Investing in the right tools can help you quickly identify and address any potential issues before they evolve into bigger problems. Additionally, having access to comprehensive analytics data can help you make informed decisions about where to focus your efforts for maximum efficiency. Agile Methodology This method encourages teams to break down tasks and projects into small, manageable chunks and test them before releasing. Using an agile process, developers can focus on building the product in short cycles while maintaining quality standards. Additionally, agile processes allow for quick feedback from stakeholders to ensure that the product meets their needs. Finally, by utilizing an iterative approach with frequent releases, startups can reduce risk and ensure that problems are caught and addressed as early in the process as possible. Continuous Integration (CI) Continuous Integration helps to ensure that the product remains stable, even as new changes and updates are introduced. CI allows developers to run tests on their code changes before they are merged into the principal repository, so that any issues can be identified and addressed quickly. It reduces the risk of significant problems occurring further down the line and clearly understands their development cycles. Additionally, We can set up a CI environment easily with modern tools. Testing Early and Often By testing the product throughout the development cycle, teams can identify and address issues sooner and with less effort. Additionally, regular testing can prevent costly mistakes from making it into production and ensure that the product meets a certain quality standard. Finally, testing early and often can help startups save significant amounts of time in the long run by identifying and fixing problems before they become substantial. Collaboration Throughout the development cycle, teams must constantly communicate and keep all stakeholders informed of changes and progress, ensuring that everyone involved in the project clearly understands what needs to be done. Additionally, collaboration allows developers to quickly identify and address issues as they arise, preventing any significant problems from occurring further down the line. Finally, collaboration ensures that teams are on the same page throughout the process, which helps speed up development cycles and ensure quality results. Hire Competent QA Professionals Finally, having competent QA professionals on your team is essential for ensuring that your product meets the desired quality standards while still moving quickly through the development cycle. When hiring, look for individuals with experience in agile development processes who understand the importance of speed in tech startups. You can streamline your QA process with the help of the right professional to ensure that your product is release with minimal bugs and maximum customer satisfaction. Conclusion The quality assurance process is essential to the success of any tech startup. By taking a proactive approach, startups can ensure that their products meet the highest standards while maintaining an efficient development cycle. The strategies mentioned above help to streamline QA for tech startups. By following them, startups can ensure that their products are up to the highest standards while allowing them to move quickly and efficiently in their development cycles. With QAonCloud, you can quickly set up a CI environment, automate tests and simulations, and collaborate effectively to ensure your product is up to the highest standards. Start building quality products with QAonCloud today!"
How Continuous Testing Is Beneficial To Your Digital Transformation Journey"Using the right testing approach can greatly enhance testing quality and efficiency as businesses move more towards agile techniques and DevOps integration. Businesses are undergoing digital transformation, which requires a strong and foolproof test plan to ensure maximum effectiveness and reduce software failures. Companies no longer have the time luxury they did with the conventional SDLC testing strategies leaving continuous testing as the only option. Continuous Testing for Digital Transformation A study by Forrester and DORA DevOps Research and Assessment implied that Continuous testing is becoming crucial for the success of DevOps and other phases of digital transformation. Ensure that continuous delivery aligns with testing strategies and that every step of the development process thoroughly ingrains product quality through continuous testing. This testing also drastically shortens the time developers get feedback on what they've delivered, combining traditional manual tests performed at various phases. Achieving higher quality eventually removes legacy procedures from your software development and testing cycles and uses new technologies and tools for more agile workflows. Benefits of Continuous Testing for Your Business Require continuous testing if your firm is using or considering a continuous delivery approach while maintaining the highest quality standards. Adopting this approach will enable your teams to thoroughly maintain quality assurance, with each test occurring as early in the application's lifecycle. Improved Quality Assurance Continuous testing ensures the application maintains quality assurance throughout the application’s lifecycle. With each test occurring early, the risk of bugs is greatly reduced. Automation technologies make it possible to carry out testing early, frequently, thoroughly, and broadly. Increased Productivity and Efficiency Integrating continuous testing into the development process leads to increased productivity and efficiency for the team. Advanced bug detection tools speed up the process of identifying and addressing glitches, errors, and vulnerabilities. This results in a faster development speed and streamlined procedures, leading to higher-quality products. Reduced Business Risks This testing minimizes the risks associated with the failure of an application after deployment. This is especially important for businesses with a large number of customers. The use of user-friendly and flexible tools decreases business risks and allows for quick adaptation to shifting business needs. Increased Responsiveness and Flexibility This approach provides IT businesses with the adaptability and production readiness needed to react quickly to market developments. The more responsive this model is, the easier it is to accelerate growth and compete in the digital age. Enhanced Competition Keeping pace with the competition is made easier in testing. The frequent release of new products and updates, combined with the use of advanced tools, leads to a faster development speed and streamlined procedures. Accelerated Digital Transformation Integrating continuous testing into the development process helps businesses get one step closer to realizing their digital transformation objectives. The use of advanced tools leads to a significant decrease in business risks and the ability to adapt quickly to shifting business needs. Conclusion Agile, DevOps, and digital transformation will continue to grow and spread. Businesses must begin their digital transformation journey as soon as possible to stay market relevant and competitive. Without a continuous testing strategy, digital transformation initiatives will fail regardless of the tools and processes utilized. Together, digital transformation, Agile, and DevOps are creating a future in which innovation drives all business operations. But for this picture to be fully comprehensive, ongoing testing is required. Organizations will proactively address bugs and promote product stability if Continuous Testing is integrated with the current system QAonCloud specialists have years of continuous integration experience and can help you successfully adapt to digital transformation with tools, such as Jenkins, Bamboo, Microsoft TFS, and more to meet your testing requirements."
Can Performance Engineering Replace Performance Testing In The Future?"In recent years, there has been a growing interest in performance engineering to improve software systems' performance. Some experts believe that performance engineering can replace performance testing in the future, as it takes a more holistic approach to performance optimization. This article discusses the various aspects of performance engineering and why it may gradually replace performance testing in the future. Performance Engineering And Its Various Aspects Performance engineering is a holistic approach to software development that focuses on optimizing the performance of software systems. It aims to ensure that software systems are reliable, deliver high performance, and are easy to maintain. Performance engineering aims to identify and address performance issues before they become major problems. We can accomplish it by considering performance at every stage of the development process, from design to deployment. Aspects of Performance Engineering Mostly Performance engineering typically includes various activities such as performance testing, performance monitoring, and performance optimization. Performance Testing Performance testing is an important part of performance engineering. It is a type of testing used to evaluate a system's performance under specific conditions. This helps identify and address performance issues we may have missed during the development process. There are various types of performance testing, such as load testing, stress testing, and endurance testing. Performance Monitoring Performance monitoring is another important aspect of performance engineering. This involves monitoring the performance of a system in production to identify and address performance issues that may arise. Testers can use performance monitoring tools to gather performance metrics, such as response time, throughput, and resource usage. We can also use these metrics to identify and diagnose performance issues. Performance Optimization Performance optimization is the final step of performance engineering, and it involves identifying and addressing performance issues we have identified during performance testing and monitoring. This could include making code, architecture, and infrastructure changes to improve the system's performance. Advantages of Performance Engineering There are many advantages to using performance engineering, including Early Identification And Resolution Of Performance Issues Performance engineering allows developers to identify and address performance issues early on, before deploying the system. This is known as "performance by design," where we analyze the performance at every stage of the development process. By catching performance issues early on, developers can make changes to the code that will positively impact performance, ultimately saving time and money in the long run. Tailored Optimization Performance engineering allows developers to optimize the performance of a system in a way that is tailored to the specific needs of the system. This approach ensures that the system is running at its best possible performance. Improved Scalability Performance engineering can be used to identify and address scalability issues early on, before they become major problems. With this, developers can ensure that the system is able to handle an increasing number of users and transactions. Cost Savings By identifying and addressing performance issues early on, performance engineering can help to save time and money in the long run. This is because performance issues that are identified later on in the development process can be more difficult and expensive to address. Improved Reliability Performance engineering can help to improve the reliability of software systems by identifying and addressing performance earlier in the development phase. This can help to reduce downtime and improve the overall user experience. Improved Customer Satisfaction Performance engineering can help to improve customer satisfaction by delivering software with high performance and reliability. Users will be able to access the system more quickly and reliably, which can help to improve the overall user experience. Improved Compliance Performance engineering can also help to ensure that software systems comply with regulatory requirements and industry standards. This can help to ensure that the system is secure and that sensitive data is protected. Improved Productivity Performance engineering helps to ensure that software systems are running at optimal performance, which can improve the productivity of users. Additionally, by addressing performance issues early, it can prevent discontinuity in business operations and render reliable software solutions. Scope of Performance Engineering in the Future The future of performance engineering looks promising, as the demand for high-performing software systems continues to grow. With the increasing complexity of software systems, and the constant need to optimize performance, the role of performance engineering will become increasingly important. As technology and development processes continue to evolve, the future scope of performance engineering will also change. With the growing adoption of cloud computing, performance engineering will play a key role in ensuring that software systems are optimized for cloud environments. Additionally, as the Internet of Things (IoT) and edge computing become more prevalent, performance engineering will play an important role in ensuring that software system optimization happens for these types of distributed environments. As more organizations adopt DevOps and Agile development methodologies, performance engineering will need to adapt to the increased speed and automation required in these processes. Another future scope of performance engineering is in the area of Artificial Intelligence (AI) and Machine Learning (ML). These technologies will bring new challenges for performance optimization, and it will be important for performance engineers to develop new techniques to analyze and optimize the performance of AI and ML-based systems. Final Thoughts Overall, performance engineering will continue to be an important approach to software development, as the need for high-performing software systems continues to grow. With the evolving technology and the increasing complexity of software systems, performance engineering will play a crucial role in ensuring a satisfactory user experience with excellent software performance. Our teams at QAonCloud have mastered the skills and knowledge to employ performance engineering to create an elevated user experience. If you are looking for a reliable partner for your performance engineering requirements, contact us for a 15 min free demo."