Webomates provides a cloud-based AI software testing as a service platform to carry out software functional testing in guaranteed timeframes. The platform creates test cases & scripts and executes them using multiple testing execution techniques like AI Automation, Automation, Crowdsource & AI enhanced manual. At the end of the execution what you get is the actionable triaged defects. Every execution result is recorded and auditable from the CQ portal.
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.
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%.
Competition creates pressure. Today, teams are under enormous pressure to deliver releases with increased speed and quality.
According to GitLab’s research, nearly 60% of survey respondents said their organizations deploy multiple times a day, once a day, or once every few days. Just 11% said they deploy once a month and only 8% said every few months. This highlights how important it is to be agile — both in development and testing.
Top reasons why Enterprise testing fails
Yesterday’s software testing practices can’t keep up with the pace of development and changing business priorities today. Most companies fail to recognize the constantly evolving testing landscape, and the required steps to overcome it.
If your team is struggling, it’s probably because of one or more of these issues.
Lack of Testing due to Unrealistic Time Expectations
Development teams manage, enhance and validate applications in a short sprinted Agile framework and release them to the end users with limited regression testing. This lack of testing translates to a False sense of Quality — thereby a failure to deliver the fanatical experience they promise.
Regression testing plays a crucial role in achieving a stable version of the software by finding defects before production deployment.
Pro Tip: With its 3 types of regression testing services, Webomates CQ is really quick in initiating the regression in just 3 minutes based on the regression type, platforms, and the target environment selected.
Outdated Test Cases & Suite
The number of changes in the testing code is proportional to the changes made by the developer in the application. It is very difficult to identify which test cases should be modified or added.
You need Self-healing scripts that help in test script maintenance by automatically detecting and resolving issues that arise during the execution of test scripts.
Pro Tip: Webomates CQ provides patented AiHealing which is carried out during the software regression cycle within the 24-hour or 8-hour window.
Lack of Exploratory Testing
As test case-based testing follows a predefined script, there are chances that a bug may not fall in the script’s scope. To overcome this challenge, you need Exploratory testing using a rotating vector-based approach that pushes the envelope in each regression looking to find new defects in the software release that are outside of the defined test cases.
Pro Tip: Webomates leverages the strengths of exploratory testing on top of test cases in regression testing to expand the scope of the test and take the quality to the next level.
Enormous Amount of Time Lost in Defect Triaging
Defects are bound to be detected while boosting feature velocity, but the key is to find them early before production. The best way to achieve this is by setting up a proper tracking system that can identify defects at the right time (as early as possible), triage them, and report them to the concerned stakeholders to improve the quality process.
Pro Tip: Webomates Defect Triaging feature shares a comprehensive triaged defect report that includes defect summary, steps for replicating the defect, a video of actual bug instances, priority suggestions, and test cases mapped with the defect.
Not Embracing Shift-Left Testing
The cost of fixing a defect rises exponentially as you move closer to production, along with compromised user experience, functionality, and security. One way to mitigate risks and eliminate surprises is by performing Shift-Left testing — where UI, API, load, and security testing are done early on rather than towards the end of application development.
Pro Tip: This makes it a lot easier to identify and fix the defects in the staging environment itself, enabling faster, better, and quality applications.
Engage in Test Automation
Focusing on manual testing can slow down the testing process and lead to inconsistent test execution, mainly when dealing with repetitive tasks or large-scale testing requirements. With test automation, developers and testers can automate the entire build-to-test process across all the stages of software development.
The biggest challenge for ensuring an excellent testing process and reliability is the lack of diverse and quality test data. 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.
Pro Tip: Use Generative AI to prepare extensive data sets including edge cases, thereby accelerating testing phases and enhancing overall efficiency. Additionally, you can also use Predictive analysis to create realistic test data by analyzing the existing data patterns.
Lack of Cloud Infrastructure Adoption
Managing IT infrastructure involves manual, complex, and mundane processes like setting up the servers, configuring them, deploying the applications, and managing the load whenever required. Lack of cloud infrastructure adoption can restrict scalability, flexibility, and cost-effectiveness, making it more difficult to build and maintain reliable testing environments.
Today, the cloud is a catalyst for any company’s growth. Products are now moving to the cloud, and so is Testing. Testing as a Service (TaaS) — also known as On-Demand testing service — helps you scale with agility and overcome the typical traditional testing bottlenecks.
Pro-Tip: Webomates — a cloud-based testing platform, is powered by a range of patented AI-infused tools. Take a look at this animation and know the three easy steps you can take to AI automate your application.
Inability to make intelligent and improved decisions
If you are a manager or part of the C-suite executives, you need data-driven insights that can help you make intelligent decisions. With a focus on solving critical business problems, test insights and analytics that help you improve product quality and effectiveness.
Pro-Tip: Use test insights into the entire CI/CD pipeline to understand the impact every change is having on the product. It also provides guidance and strategic benefits to test management.
Testing for the Future: How can Webomates Help?
User expectations are rising, and you need intelligent solutions to assist you in dealing with these challenges. You need to modernize the company with technology that promotes creativity and innovation, improves customer experiences, and equips the employees with the knowledge and tools necessary to make informed business decisions.
Identifying the gaps is the first step in moving forward. The next step is to create a plan and choose a service/tool that can assist you in bridging all of these gaps. AI-based testing helps to predict the best testing approach, anticipate and prevent mistakes, and enable the pace and scope of software releases.
Webomates is a complete Testing as a Service (TaaS) provider. Its cloud-native platform helps teams overcome the complexities of testing applications built using advanced technologies and perform both functional and non-functional tests.
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?
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.
Flexibility: Selenium is a tool that is widely used for its flexibility when needed to perform functionality tests or rapid regression testing.
Multi-Language Support: Selenium allows users to test codes written in C++, Java, Python, and Ruby, offering extensive language support.
Cross-browser compatibility: Selenium supports test case implementation across different browsers.
Open-source: It is an open-source framework and it’s free! The selenium users can leverage the platform.
Challenges of Selenium Testing
Although Selenium offers a pretty stable environment for automation testing, there are many bottlenecks. These pain points can have an impact on the overall testing efficiency.
Selenium & The Future of Software Testing — Driving Value with Intelligent Automation
To 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 creation
For 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 Maintenance
If 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 Testing
APIs 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 Testing
The 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 capability
Test 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 –
Detection Phase — Their Test Package analyzer detects the requirements change and impact to test cases and the Defect Analyzer detects the script level changes/abnormalities in the existing code and automatically fixes them without human intervention.
Generation Phase — This involves analyzing and regenerating the test cases and scripts.
The Way Forward
The testing industry started using Automation and AI in dribs and drabs — either to handle repetitive tasks or automate routine functions. Today companies are avant-garde in AI — meaning they are in favor of introducing new and experimental ideas and methods to increase the testing efficiency.
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.
