Software testing is a crucial step in ensuring an application’s reliability and functionality. As you increase test coverage, the quality of your application testing will increase. Regression testing and end-to-end testing focus on several testing facets to guarantee complete end-user satisfaction.
While End-to-End Testing focuses on the testing of the entire user flow and integrated components, Regression Testing targets specific functionalities and validates the impact of code changes. You need to understand their differences to implement an effective testing strategy. Key Differences Let’s consider an example of a banking application, and look at some of the differences. When do you need End-to-End Testing? Think of End-to-End Testing as a detective — examining the app’s interface, testing the user’s journey from initial login to the successful transaction completion. Pro Tip: Webomates offers code coverage as an optional add-on to AI test automation. Follow these 8 best practices to master end-to-end testing to ensure a seamless user experience and better product quality. When do you need Regression Testing? Regression testing is more like a time traveler — traversing across different versions of the application, ensuring that the previous application functionalities are still preserved today even after new changes. A change in code due to any of the changes made by developers, security, or any other teams could have a domino effect that can affect the whole application. Pro Tip: The process of regression testing includes selecting the right test cases, and determining the testing frequency and types of regression required to be carried out. Webomates helps you scale up by getting build checks done via its 3 types of regression testing services that provide the maximum quality. Business Benefits They Bring How can Webomates Help? Regression testing and end-to-end testing both play crucial roles in assuring a seamless and error-free user experience, all while protecting your application against potential vulnerabilities. As a cutting-edge cloud-based Testing as a Service platform, Webomates uses AI to reimagine the testing process. The patented tool like AI Test Strategy and Creator tool help you in devising a well-rounded test strategy for the software. By creating and automating the appropriate test cases, their AI Modeller engine can help you cut the human work required to write or maintain the test suite by more than 50%. To find out more about what Webomates Intelligent Testing services can do for your business, get In touch with us today. Please click here and schedule a demo, or reach out to us at [email protected] Tag : End to End testing, end-to-end testing and regression testing, End-to-End Testing vs. Regression Testing, Regression Testing, Software Testing
0 Comments
Isn’t this an everyday scenario?
You are building a complex application with intricate architecture. Business requirements keep changing and the development and testing teams are always under immense pressure to design, build, test, simulate and deliver a high-quality defect-free product. However, you feel your team lacks skills in effectively testing the applications in a short span of time which in turn is hampering the overall product time-to-market. Due to the relentless need for faster releases, teams need to balance between speed and quality. So what do you possibly need to help your testing teams with so that they gain the competitive edge? Automated testing = An Automation framework + Speed + Agility + Scalability You need a strong automated testing framework that can help you transform testing into a continuous and efficient end-to-end quality engineering function. Most of the teams use Selenium for their automation testing needs. Tools like WebDriver, Selenium Grid, Selenium Integrated Development Environment (IDE), and Selenium Remote Control (RC) are popular. Why is Selenium so popular?The Selenium testing tool is used to automate tests across browsers for web applications. It offers many benefits and due to these multiple features, Selenium is still considered to be a promising automation testing tool for the future.
Selenium & The Future of Software Testing — Driving Value with Intelligent AutomationTo overcome these challenges, you need more predictive and intelligent testing approaches based on automation and innovation. Next-gen technologies like AI and ML are transforming the testing industry and helping to propagate improved testing capabilities. According to Gartner, By the end of 2024, 75% of organizations will shift from piloting to operationalizing artificial intelligence (AI), driving a 5 times increase in streaming data and analytics infrastructures. AI-based technology is helping enhance testing with the following capabilities: 1. Automated test case creation/ script creationFor you to test your application precisely, you need test data that is similar to production data. However, creating such data sets is one of the biggest challenges the testers face. With the advances in AI, we can eliminate such inefficiencies. AI can easily generate test data for you by analyzing the UI and identifying a series of test cases that predict user behavior! Test data is the generation of data that comes as close as possible to your production data without revealing any sensitive information — all guided by artificial intelligence and analytics. 2. Test MaintenanceIf you need to run automated tests, then you also need to invest in test maintenance. With every change in the application, you need test maintenance for the existing tests. This is the greatest bottleneck in the testing process. With AI, you need not worry about maintaining the test suite and test script. The self-healing capability helps you detect the problem before they arise! 3. API TestingAPIs are the behind-the-scenes of an application and hence testing them is very crucial for the application’s functionality. However, testing API requires a high degree of specialized technical skills along with domain and architectural knowledge. API Testers need to spend a lot of time understanding how the API works and building test cases. Using AI for API Testing can take out this complexity and give a significant boost to the quality of testing. The AI can analyze and build API tests and scenarios — without the need for the tester to have an in-depth understanding of the architecture. 4. Image/Visual TestingThe first thing a user notices is your application’s UI. When new changes are introduced, the application’s UI keeps changing — either due to the ever-changing requirements or during the integration or build process. The changes could be as minor as the color change, shape, and size of the buttons and text! It’s highly difficult to validate these changes manually on every page. AI and ML help in recognizing the patterns in images and help in detecting the differences, making UI testing faster and more reliable. Healenium is a testing framework that improves the stability of Selenium-based tests. Web applications are constantly updated. So all automated UI tests will face locator changes due to the web page changes. It’s an AI-powered library that solves and fixes locator changes. As the locator issues are fixed in run time, it improves the stability of the automated tests and ensures your CI/CD pipeline is always Green. 5. Self-Healing capabilityTest flakiness — the enemy of every tester! The reasons for test flakiness could be anything — no correct testing framework, lack of maintenance, dynamic elements, co-dependent or badly written tests. And if you are using Selenium, incorrect object identifiers are always going to be an issue. This is because Selenium does not have any self-healing capability that can identify such flaky elements and fix them. The automation may fail due to the predefined test scripts. It is then very difficult to identify which test cases should be modified or added. Fret not! The AI ML power combo can help you overcome this flakiness. With the self-healing capability added to the framework, it can learn if there is a change made, and then automatically modify the test automation script to fix the problem. Tools like Webomates-CQ apply AI and ML algorithms to the self-healing test automation framework to dynamically adapt their testing scope to the changes. With their 2 phase healing –
Adding AI and ML to testing has empowered the development and testing teams to improve efficiency across functional and non-functional aspects of the application. With Continuous Testing at the center stage of all software development activities, these innovative AI and MLpowered tools and technologies help to speed up the release cycles by identifying, predicting, and rectifying defects even before they reach the customers. What’s In It For You?If you want to execute different types of software tests in a limited timeframe, with detailed analysis and insights, Webomates-CQ is the right tool for you! To solve complex issues, we have innovative AI solutions like defect prediction, test case maintenance, codeless testing, exploratory testing, test insights, and many more. Webomates CQ is an ingenious AI-based testing tool that delivers all of the above with the service level guarantees to support its claims. Webomates provides intelligent automation solutions with intelligent analytics. It leverages the power of data processing, analysis, reasoning, and machine learning to provide an end-to-end testing solution for your business. If you are looking for a one-stop solution for your testing needs then look no further, reach out to us at [email protected]. If you liked this blog, then please like/follow us Webomates or Aseem. The Need for Speed: Ensuring Agility with Incremental Release
In a quest to deliver features faster, achieve higher flexibility, better satisfy customer requirements and overhaul competition, organizations are breaking through the barriers of traditional software development processes like Waterfall model, and instead taking the Agile DevOps path which is both iterative and incremental. Thus, there is a huge emphasis on shipping software faster. This transformational journey involves removal of silos between the development, testing and operations teams, and applying shift left principles. Does this mean that we can achieve Zero Production defects? Though a fairytale dream of every organization, the Lean Software Development: An Agile Toolkit quotes: “One of the fastest ways to kill motivation is what is called in the US Army a zero defects mentality. A zero defects mentality is an atmosphere that tolerates absolutely no mistakes; perfection is required down to the smallest detail. The army considers a zero defects mentality to be a serious leadership problem, because it kills the initiative necessary for success on a battlefield” — Mary & Tom Poppendieck Thus, instead of “zero defects”, the agile organizations are all about continuous planning, continuous testing, continuous integration with ‘continuous’ being the focal area. Integrating Software Testing in your Incremental Release The incremental build model is a method of software development where the product is designed, implemented and tested incrementally (a little more is added each time) to enhance the product with improved functionalities. It addresses the time-to-delivery of software products. But, how do you know if your incremental build is ready? Delivering software incrementally necessitates the Development and QA teams to work collaboratively to deliver a build. Though the nuances of day-to-day operations may vary from organization to organization, the teams adhere to the same core tenets to ensure incremental release — Continuous Integration, Continuous Delivery, and Continuous Deployment. The objective is to get feedback to the developers earlier & faster to help isolate issues enabling reliable and frequent delivery of code changes. How we Do It @ Webomates CQ Webomates CQ becomes an integral part of the product development process right from its initial development to its final release. To ensure a successful ship of the minimally viable feature, Webomates CQ conforms to an Incremental Build Release Criteria by providing functional testing with CI/CD, Modular and Full. Webomates believes that the Build Release Criteria should be SMART — Specific, Measurable, Attainable, Relevant, Trackable, to know if your build is ready. It ensures every build satisfies the below Criteria: TestOps — The Webomates advantage With its patented tools — Webomates CQ along with AI Defect Predictor tool, Webomates ensures that for a build with release notes, all committed test cases on all browser/smartphone/tablet will be executed in the committed time. This remains true regardless of software builds that modify features, defect fixes that modify test cases/scripts, and automation timeout errors. Webomates is fully configurable to the needs of the application and the Development Teams exhibiting agility in scaling up its testing services based on the changing requirements.
For 300 test cases with a failure rate of 35% (105 failed test cases), it usually takes 12 hours to triage the results and identify the false positives. Using the Defect Predictor, the time taken drastically reduces to 2–3 hours. Business Impact: Conclusion: For every incremental build, Webomates CQ can create, execute, maintain, analyze test cases and generate defects for browsers, mobile, Windows and API applications. Exact state of the system in terms of bugs is known after every check in. For each build, Webomates ensures that the following guarantees are met in a fixed interval of time: With such stringent code quality checks, the defects are detected at an early stage hence are easier to fix, ultimately resulting in improved code quality and timely delivery of the product. Read our articles on Shift Left Testing in Agile and Skip Security Testing at your own risk to understand how Webomates can helpWith the power combination of Webomates regression testing with you in building a good product where UI, API, Load, and Security are not left out to be tested as a different component at the end. If you are interested in learning more about Webomates’ CQ service please click here and schedule a demo, or reach out to us at [email protected] Cloud migration is the process of moving applications, processes, data, and other related components from on-premises servers to a cloud-based infrastructure.
Advancement in technology in the past few years has led more and more businesses to move their products and applications to a native cloud setup. Cloud migration helps in reducing an organization’s operational and infrastructural costs, thus improving the effectiveness of the overall development and deployment process. This move makes way for the teams to focus on addressing the demand for faster time to market with improved quality. Our article will walk you through the benefits attached with cloud migration, followed by the challenges that it poses, along with the ways to overcome those challenges. Why migrate to the cloud?“Worldwide end-user spending on public cloud services is forecast to grow 18.4% in 2021 to total $304.9 billion, up from $257.5 billion in 2020” — Gartner, Inc. In the year 2020, the Covid-19 crisis had given rise to the need for remote connectivity. Organizations in various sectors set aside a good portion of IT expenditure to address the remote working needs and to keep the wheels rolling for their business. However, even before the pandemic, the cloud was in high demand due to the benefits it provides for overall business growth.
Challenge Summary Initial setup costThe cost incurred initially for the setup and recurring costs can be a decisive factor for cloud migrationValidating the stages of cloud migrationEvery stage of migrating the application to the cloud has to be validated carefully for continuous availability and correct functionalityVendor Lock-in issuesSwitching between cloud vendors is not that easy, as it involves additional cost and loss of time and resources.Workforce related issuesAccepting the change by the teams is a common challenge that organizations have to deal withBusiness valueClarity on why migration is being done and its overall business value have to be carefully listed down to prepare a comprehensive migration plan. Initial setup cost Overall financial implications of cloud migration can be a decisive factor. Cloud migration reaps benefits in the long term, by reducing the maintenance and infrastructure costs with improved processes and efficiency. However, there are initial investments that are needed, which include:
Solution The business decision-makers should work in tandem with the technical team to identify the initial costs involved and day-to-day expenses. Key performance indicators for cloud migration should also be established and checked regularly. Evaluating the costs and weighing them against the KPI’s regularly gives a good idea of the success of cloud migration and also indicates problems if any. These numbers will aid in regulating the expenses as per the budget earmarked for migration. Validating the stages of cloud migration Due to the initial efforts and costs involved, many organizations tend to opt for an incremental approach towards cloud migration. Migrating stagewise can pose certain challenges since every stage has to be validated for the operability and continuous availability of systems with correct functionality. This is compounded by the fact that there could be multiple applications at different scales, small, medium, or large, that need to be validated. Besides this, migrating all the system operations and transferring zettabytes of data is not an easy feat. Solution It is a good idea to conduct an IT audit for identifying the scope of cloud migration to define a proper strategy that outlines the costs and process of migration. It is prudent to ensure that all the integration points for databases, third-party tools, application gateways, etc have been accounted for. Also, having an overlap of operations on-premises and on the cloud will address the issue of continuity. Webomates provides a seamless migration to the cloud ensuring smooth operability with no or minimal impact. One of our prestigious clients had a cloud migration challenge at hand. Read more about it on our website by clicking here. We helped them in managing migrations for around 140 applications, including SAP, that was impacted by the migration. Many of these applications, if impacted, would have cost them dearly. Vendor lock-in issues Many organizations are concerned about being locked into a single cloud platform. It stems from the fact that portability is at stake in many cases, especially for legacy applications. Sometimes, organizations may want to switch the cloud vendor due to multiple reasons but are deterred due to the clauses in SLAs or because of the lengthy and expensive process for changing the vendor. Solution It is a good idea to research the vendor policies, services, and contract renewals before making final decisions regarding migration. Another option is to put an exit clause in the SLA. In either case, it is good to have a technical exit strategy in place, which includes improving portability of data, code, and processes, including detailed documentation. Workforce related issues It is a human tendency to resist any change. Cloud migration brings its own sets of roadblocks, like technology changes and revised work strategy, which may lead to discontentment among the teams. Solution Addressing the employee concerns, educating them about the changes, and training them suitably to rise to the challenge is the best way to handle such a situation. Business value Cloud migration is a key turning point for any organization. While it is important to work on the “how” of migration, it is equally important to understand “why” too. Lack of clarity on why migration is being done may prove disastrous in the long run. Solution Analyzing the need for cloud migration and listing down its business value and ROI is an important step. It is important to take into account the current infrastructure, process, and skillset while defining a robust migration strategy. ConclusionBusinesses migrating to the cloud is the new normal now. It has become more of a necessity these days to have an edge in this highly competitive world. Cloud migration has opened the doors of opportunities for organizations to leverage ready accessibility, scalability, and collaborative capabilities, thereby reducing overhead costs and providing increased efficiency. Webomates provides Testing as a service with a hybrid model of automated, crowdsourced, and load testing system in the cloud setup. Our team is well versed in various cloud technologies. The entire dev team, as well many team members of the testops team are AWS certified and are well equipped with the necessary knowledge needed to execute testing services with ease. At Webomates, we work relentlessly to evolve our platform and processes to provide guaranteed execution, which takes testing experience to an entirely different level, thus ensuring a higher degree of customer satisfaction. If you are interested in learning more about Webomates’ CQ service please click here and schedule a demo, or reach out to us at [email protected] Read the Next Blog Ad hoc testing Continuous testing tools in DevOps Functional Testing Api testing Shift left testing DevOps testing Intelligent test automation OTT media testing services Requirement traceability Black box testing Regression testing Software Testing Life Cycle Test Automation vs Manual Testing Selenium Testing Automation Exploratory testing in software testing Did you know that the term Smoke testing has its origin in electronic hardware testing?
It was as simple as looking for any signs of smoke when the hardware under test was plugged in. If you see smoke, then it is clear that the circuitry has some major issue and cannot be tested any further till the problem is rectified. Drawing a parallel in software testing, once a build is ready to go for QA, an initial test is done to check whether it is worthy to be released for the next level of testing. Interestingly, there are some other versions of how the term came into existence, you can read about them on Wikipedia by clicking here. What is the need for Smoke testing?The purpose of Smoke testing is to identify issues/bugs in the preliminary stages and ensure that a stable build goes to the QA team for testing. This not only makes the testing process efficient but also saves a significant amount of effort and time spent by the QA. The figure below summarizes the process in the simplest possible way. There are marked benefits to including Smoke testing as a part of your DevOps strategy. Some of the benefits are listed below for quick reference. Checklist for effective Smoke testingSmoke testing should be a carefully planned activity. It is always a good idea to have a customized checklist as per your organization’s QA process. In this section, we are listing down general guidelines to be followed. You can add more to this list as per your organization’s testing protocols.
How Webomates can help in smoking out bugsWebomates CQ leverages the power of AI/ML to provide a complete testing solution with intelligent analytics and guaranteed execution SLA. Webomates CQ can seamlessly integrate with your current CI/CD pipeline and can execute smoke tests within 15 minutes to 1 hour. Let us take a quick look at how we can help in easing Smoke testing for your organization. Our AI Modeler engine can help organizations in generating and automate the right test cases. Webomates’ patented AI Defect Predictor can identify false failures with 99% accuracy. A detailed report along with an in-depth analysis of test results is shared with all the concerned teams. Our ingenious AI Defect creator automates the process of gathering the data for a defect, including the key 20 seconds of video that shows the defect occurring. This helps in a significant reduction in time spent in defect triaging. If this has piqued your interest and you want to know more about our services, then please click here and schedule a demo, or reach out to us at [email protected]. If you liked this blog, then please like/follow us Webomates or Aseem The fusion of human ingenuity and AI
Gone are the days when you could only rely on traditional methods for safeguarding nations. Today’s defense forces carry out challenging and intricate tasks under erratic and dynamic conditions resulting in an urgent need for modern development and testing strategies. To succeed, the defense needs to build human intelligence which is aided, enhanced, and augmented with AI and ML capabilities. AI can enhance the testing and quality assurance (QA) processes to ensure improved reliability, precision, and security of crucial defense operations. Let’s explore the value of AI testing for defense and understand why a strong QA plan is necessary for more intelligent defense solutions. A Quick Look at the Failures in Defense Due to Lack of Quality Testing There are numerous examples of potential consequences of insufficient application testing in the U.S. military. All these errors could have been avoided if the systems were properly tested and validated. According to the Artificial Intelligence in Military Market report, AI in the military market is estimated to be USD 9.2 billion in 2023 and is projected to reach USD 38.8 billion by 2028, at a CAGR of 33.3%. Priority Outcomes through AI How can testing solutions help defense? Our objectives and priority outcomes are to: Unleash defense potential with the power of AI Through the adoption of AI-enabled testing, our Armed Forces can modernize and rapidly transition into an agile and intelligent force. Surveillance and threat monitoring Defense forces capture massive amounts of surveillance data and confidential intelligence from a variety of sources and IoT-connected equipment, such as satellites, drones, radars, and cyberspace. By integrating IoT automated testing into such surveillance and threat monitoring systems, defense forces can validate the reliability of these systems, identify any patterns and monitor potential threats. This allows for effective and proactive defense tactics and increased threat response capabilities. Enhancing Defense Communications The defense sector relies heavily on effective communication for successful mission execution, coordination among forces, and ensuring real-time situational awareness. Testing an ecosystem of intelligently connected devices poses significant challenges. Functional Testing, which includes Performance testing, Cross-browser testing, and cross-device testing allows the defense systems to undergo extensive testing, minimizing the risk of catastrophic failures during mission-critical operations. For functional and Usability testing, Webomates has an IoT lab setup for intensive testing of the functionality, usability, accessibility of heterogeneous devices, and networks of these IoT devices. Accelerating Application Efficiency Time is of the essence in the defense sector. AI-powered Intelligent Automation Testing solutions will empower the entire force since they will reduce redundant workloads. Defense forces can deploy new systems and updates faster, and also ensure timely response and adaptation to new threats and challenges. Shift Left Testing speeds up software releases by testing frequently and early in the development process. This method finds issues faster and reduces unexpected outcomes at the end of development. Mitigating Cybersecurity Risks One of the critical defense applications for AI technology is cybersecurity, as these attacks can lead to the loss of highly sensitive and confidential data. By leveraging AI testing, defense forces can strengthen their cybersecurity and protect their assets, ensuring that sensitive data is secure and the organization is not compromised You can take the help of Webomates’ penetration testing, Security testing, Exploratory Testing, and Performance Testing and prevent such cyber attacks. Strategic Decision Making Decision making especially in high-stress situations is difficult. And defense forces rely on systems that use AI and ML algorithms to analyze historical and real-time information and interpret data. These systems need to undergo extensive testing to be able to evaluate risks and help the forces make informed decisions. Optimizing Resource Allocation The defense sector works with the motto — ‘Do more with less’ as it operates under strict timelines along with budgetary constraints and must make optimal use of limited resources. Depending on the requirements of the application, Regression testing along with Exploratory testing can be done on various scales. By pinpointing bottlenecks and highlighting potential improvement areas, they offer valuable test insights into system performance. As a result, defense organizations can optimize their operations, reduce costs, and ensure the most efficient use of resources. Preventative maintenance of warfare systems With AI-powered testing techniques, defense forces can switch from reactive to proactive maintenance strategies. AI testing techniques like defect prediction and self-healing testing can be used by warfare systems including weapons, sensors, navigation, aviation support, and surveillance to identify deviations from expected behavior and take immediate remedial actions. This proactive approach enables teams to handle problems in advance, which reduces downtime and helps them avoid costly consequences. Secure Software Development and Testing By automating code validation, deployment validation, and test execution, AI testing can decrease manual effort and improve system resilience as a whole. Continuous testing is an integral part of the CI/CD pipeline, that can be integrated into the defense application’s development lifecycle. Combined with Shift Left Testing, it ensures that the functionality, performance, and security of warfare systems are continuously validated. Success Story With our exemplary work with the esteemed US Air Force, we have demonstrated our ability to help organizations achieve scalability and agility while overcoming the typical traditional testing bottlenecks. Webomates has successfully completed SBIR Phase 1 and Phase 2 with the US Airforce. Webomates’ Testing as a Service (TaaS) — also known as On-Demand testing service — helps you get clear visibility into your testing data, outcomes, and valuable insights by combining applications and data into a single platform. We work with unwavering dedication to understand your unique needs and provide customized solutions to ensure the success of your application. Take a look at this animation and know the three easy steps you can take to AI automate your application. To find out more about what Webomates Intelligent Testing services can do for your business, get In touch with us today. Tag : #AITesting #StrengtheningNationalSecurity #AITestinginDefense Today is just the beginning of Generative AI and its countless benefits. Generative AI applications such as ChatGPT, GitHub Copilot, DeepArt, and others have taken the world by storm by unleashing a wave of innovation, creativity, and productivity. We are now able to do tasks that were previously unimaginable.
Generative AI – Catalyst or Replacement? Generative AI can mimic human capabilities to an astonishing level, raising fears about AI replacing humans. However, it’s important to understand that Generative AI will only empower humans and not replace them. Leaders across organizations are realizing that they can actually unlock exceptional accomplishments by nurturing this collaboration between humans and Generative AI. So what are the potential business benefits? Generative AI is being used to create new and unique content, spanning across various domains like art, music, graphics, social media, and beyond. Let us explore some of the business benefits it can offer when used in the software engineering disciplines. Generative AI Use CasesLet’s consider a scenario where a software application is being developed for a banking platform and needs to be tested. Now, let’s see how Generative AI can help us reduce manual effort, accelerate testing cycles, and help us improve efficiency across the following use cases.(Generative AI in software testing)
For the banking application example, it can generate test cases to cover various scenarios such as creating new accounts, making fund transfers between different account types, testing different transaction limits, and verifying balance.
Examples include CodeAI and GitHub’s CoPilot. They use contextual understanding, trained models, and code repositories to generate code snippets, accelerating the coding process and aiding the developers in reducing human errors. According to Mckinsey research, technology companies are already using Generative AI such as Replit which is being used by more than 20 million coders today.
For the banking application scenario, it can generate sample customer account details, names, addresses, and other required test data.
For example, it can identify inefficient algorithms or resources used in any feature that takes up the maximum CPU usage, and suggest alternative implementations that improve the execution speed. This simplification reduces the complexity of the code, making it easier to test and maintain.
For example, Webomates’ AI Defect Predictor helps the development and QA teams that use CI/CD service to reduce their triage time. This proactive approach enables the development and testing teams to correct their code and reduces the overall effort required in automation testing.
Accenture is testing the use of OpenAI LLMs to automatically generate documentation – for example, SAP configuration rationale and functional or technical requirements. Limitations of Generative AI Capabilities Although the software development and testing teams are opening up to using Generative AI in software testing, it still comes with a set of unique challenges and limitations. How Can Webomates Help? Generative AI is here. And as it keeps evolving, it will unlock new possibilities for improved efficiency and innovations. Meanwhile, we can leverage it to transform our application testing and automation efforts. Webomates understands that AI-based software testing speeds up product releases and generates the promised business value. It’s an industry- and tool-agnostic solution to optimize testing in various scenarios. Schedule a demo to discover the full potential of our AI-driven software testing solutions that can boost your business outcomes, increase productivity, and accelerate product releases. You can also reach out to us at [email protected] What and Why of Test Automation in Testing Landscape
Today, Technology and creativity know no bounds. AI, once regarded as science fiction and used as plot material for Hollywood movies, has become a near-ubiquitous technology that is enhancing our daily lives in our workplaces, homes, and across industries. The market has been inundated with a steady stream of new digital products. The latest innovations have taken the IT world by storm. You can ask complex questions to ChatGPT and receive eerily humanlike responses. You also have a program called Codex that can write computer code; just describe the kind of software issue you’re attempting to fix, and Codex will provide a code solution in the form of a line of code. The software testing industry too has undergone significant changes in recent years, with test automation becoming increasingly essential for organizations to remain competitive and deliver high-quality software. Test automation has become increasingly important for several reasons, including the speed and complexity of software development, the need for increased efficiency and accuracy, and the limitations of manual testing. According to GMinsights‘ most recent analysis, Automation Testing is now valued at USD 20 billion and is anticipated to grow at a 15% CAGR between 2023 and 2032. In this article, we will explore why test automation is so important in today’s software testing industry. Harnessing Test Automation as a catalyst for change You cannot talk about the latest practices like DevOps, Continuous Delivery and Continuous Testing without the term Automation. Applications may have defects in their usability, security, performance, or any combination of those factors. And the inevitable result of this will be a decline in market share, revenue, and customer loyalty. Test automation provides the necessary speed and scale to ensure that software releases are delivered quickly and with high quality, allowing organizations to remain competitive and meet the demands of their customers. Reducing process lead time and costs through automation of labor-intensive, repetitive tasks frees up human resources for their core competencies and revenue generating tasks. Additional benefits also include: Top Challenges for making the move to Test Automation Organizations are realizing the immense potential of intelligent automation – how it increases value and efficiency across business processes. However, few teams are finding it a grueling task to make the move. The Tricentis Software Fail Watch report states that 314 companies were impacted by software failures, affecting 3.6 billion people and costing $1.7 trillion in lost revenue. Test Automation has numerous benefits, but it comes with its own set of challenges: So, how do we Implement a Good Test Automation Strategy? Despite the fact that automation involves serious effort and dedication, success isn’t that difficult to achieve. The secret is to research, plan, and solve. One of the key needs for the industry is to provide the C-suite and organizations with a roadmap to accelerate, scale, and sustain automation testing adoption. The Test Automation Strategy defines a framework for automated test scripts. It calls for automating tests at different levels. The foundation and bulk of this test automation pyramid are unit and integration testing. Service layer or API testing is the next step, where the API tests are run against the service layer. The GUI tests, which are at the top of the pyramid, validate the application as a whole at the presentation layer. Top it up with exploratory testing that identifies potential edge cases. Unlike scripted testing, exploratory testing uncovers unique and out-of-scope defects that would have otherwise been missed. Although implementing a test automation strategy requires significant time and resource commitment, the rewards can be enormous, including improved quality, lower costs, and greater efficiency. By following these steps, you can implement a successful test automation strategy that meets your specific needs and helps you achieve your goals:
Depending on the project’s needs, the development process, and the testing effort’s objectives, different types of automation tests may be employed. Let us look at the types of tests that can be automated and how they help test every aspect of the system enabling users to achieve a frictionless experience.
Video services have gained immense popularity in the past few years. They can be broadly classified into two categories: Video Conferencing and Video Streaming aka broadcasting. Their demand has skyrocketed in the last few months when the world is under siege due to the prevailing pandemic.
Live video conferencing tools, like MS teams, Zoom, Google Hangouts, Skype, etc, are being used extensively these days for conducting meetings and scheduling web-based conferences. The education field has started depending highly on various eLearning platforms, besides leveraging the video conferencing tools. Equipped with smartphones and access to the internet, the rate of consumption of video on demand is overwhelming too, be it sports, music, movies, news, or documentaries. It gives the flexibility to watch videos on the move at the time of your choice. The surge in demand and usage, in general, puts a high load on the content delivery and management infrastructure. In order to appease the current customer base and entice new ones, the product and service providers need to maintain & upgrade current infrastructure, besides introducing new measures to provide consistent and high-quality services. This gives rise to the need of having a good video testing process in place. Why do we need video testing?Imagine a scenario when an important point is being discussed in a meeting/class and the video gets paused, or the picture gets pixelated, or the voice is not clearly audible. It adversely impacts the whole user experience. The performance of the whole ecosystem of video services is vital for continued customer satisfaction and loyalty. Like every other technology, video testing is extremely important to ensure that the end-user gets maximum out of his/her investment in the tech he/she paid for. This task is considerably tough keeping in mind the rate at which the hardware (mobiles, televisions, tablets, etc.) are upgraded and the content demand keeps going up. The video content is dynamic in nature, coupled with the wide range of receiving hardware makes it a challenging task. Hence, it is imperative to have a well-outlined video testing process in place. Video streaming performance metricsVideo testing also aids in analyzing the impact of actual usage during peak times by measuring various performance metrics, thereby ensuring that the end-users can have an uninterrupted experience. These metrics form the baseline for video testing.
Bit rate is measured as the number of bits transmitted per second. A higher bit rate does not necessarily translate into better quality viewing on the receiver’s end if the hardware is not equipped to process that.While bit rate can determine the quality of audio-visuals in terms of looks, it has another comrade called, Frames per second (FPS), which determines the smoothness of the video. Just imagine watching an intense sports live and the player moves around in spasmodic choppy motion because the frame rate was not ideal. Higher frame rate means smooth videos with crisp detailing.
But the moment, buffer starts getting drained, the video stalls and re-buffering starts. This leads to a lag in streaming. Commonly known as time taken for re-buffering, this phenomenon is measured by lag length. Lag length is the time taken to refill the buffer.
Nuances of Video TestingSeveral scenarios have to be considered while planning for video testing. The following points are just a few examples that can be used as verification guidelines while embarking on the journey of test case planning. These are just some examples. A lot more scenarios can be conjured up for video testing. Fiddle as much as you can with the various functionalities and come up with test cases. Keeping in mind the above sample scenarios, manual testing and visual analysis with human intervention becomes an obvious choice. However, manual testing is time-consuming and has its own limitations when it comes to repetitive testing. That’s where automation helps. Tools like Selenium, Ruby, and Jscript can be used for video testing automation. However, it is vital to ensure that the stakeholders get the best ROI from automation. The success of automation testing is highly dependent on the infrastructure generating and transmitting the content as well as the recipient. Testing for recipients can be done on the basis of the target audience and sample data generated from it. Moreover, the test environment can emulate the real setup to a certain degree. Device and target environment diversity may pose a challenge in automation since video testing needs to address a variety of endpoints with different configurations. Also, it is important to ensure that the automation scripts are reusable and maintainable. Adaptive bitrate streaming is a way of adjusting the video quality depending on the user’s device and network connectivity. This may pose a challenge while testing the system and may lead to inaccurate testing results. Read for more Information :https://www.webomates.com/blog/video-testing/the-curious-case-of-video-testing/ Read Next Ad hoc testing Api testing AI testing platform |
Categories |