#codeless testing platform

[yethiconsulting]

UI Automation Testing: Reducing Manual Efforts and Boosting Accuracy

Introduction:

UI automation testing is a powerful method for reducing manual testing efforts while improving test accuracy and coverage. By automating repetitive tasks, QA teams can focus on more complex testing, leading to faster release cycles and higher software quality.

Automating Repetitive Tasks:

Manual UI testing can be time-consuming and prone to human error. Automating repetitive tasks—like form submissions, button clicks, and navigation—frees up testers to focus on more critical, exploratory testing. Tools like Selenium and Cypress allow you to automate these tasks, ensuring consistency across test runs.

Increasing Accuracy and Consistency:

Automation eliminates the variability introduced by human testers, ensuring the same steps are executed each time, thus improving the reliability of your tests. Automation also enables parallel testing across multiple browsers and devices, enhancing test coverage.

Faster Feedback with CI/CD Integration:

Integrating UI automation testing into CI/CD pipelines ensures that tests run automatically after each code change, providing faster feedback to developers. This helps catch bugs early in the development cycle, reducing the risk of costly errors.

Conclusion:

By automating UI testing, teams can significantly reduce manual efforts, increase accuracy, and accelerate development timelines. This leads to more reliable software and more efficient testing processes.

[qualityassurance11]

Best Practices for Successful Automation Testing Implementation 

Automation testing is an essential part of modern-day software development that accelerates delivery, reduces manual work, and improves software quality. But success in automation testing is not assured, it should be achieved by proper planning and execution along with proper compliance of best practices. 

In this blog, we will talk about key actionable strategies and best practices to ensure the successful implementation of automation testing in your projects. 

1. Start with a Clear Strategy 

Jumping straight into automation testing without a clear strategy will not always yield the desired results. Define the following: 

Objectives: Define the goals of the automation, whether it is about shorter test cycles, improved test coverage or eliminating human error. 

Scope: Set the areas of your application for automation and focus much on areas that have a high impact like regression and functional testing. 

Stakeholders: Get early involvement from the development, QA and product teams to avoid misalignment regarding expectations. 

A well-formed strategy helps guide the way and make sure everyone involved is aligned. 

2. Prioritize the Right Test Cases for Automation 

One of automation testing’s biggest mistakes with it is to use automation for everything. Rather than that, shape your test cases to that of: 

Are monotonous and time-consuming. 

Wherein critical for application functionality 

Have stable requirements. 

Some of these tests are regression tests, smoke tests, data-driven tests, etc. Do not automate the exploratory or highly dynamic tests that often get changed. 

3. Choose the Right Automation Tools 

The effectiveness of your automation testing initiative highly relies on appropriate tools selection. Look for tools that: 

Support the technology stack of your application (e.g., web, mobile, APIs). 

Give the flexibility to expand your project. 

Offer extensive reporting, reusability of scripts, and run across browsers. 

GhostQA is one example of a codeless platform that works well for teams across the skill set. GhostQA can let you focus on what matters and Auto Healing reduces your maintenance to enforce. 

4. Build a Strong Automation Framework 

An automation framework is the backbone of your automation testing process. It helps in standardization, reusability and scalability of test scripts. So, when you start designing your framework, make sure to leave some room for these features: 

Modularity: Split test scripts into reusable components 

Data-Driven Testing: Use Data-Driven Testing to separate test data from the scripts to provide flexibility. 

Error Handling: Install anti-malware solutions to prevent potential threats. 

A good framework streamlines collaboration and makes it easier to maintain your tests. 

5. Write High-Quality Test Scripts 

A good test script decides the reliability of your automation testing. To ensure script quality: 

When naming scripts, variables, or methods, use meaningful and descriptive names. 

For adaptability, you should leverage parameterization instead of hardcoding these values. 

Set up appropriate error-handling procedures for handling unforeseen problems. 

Do not add anything unnecessarily, the more complexity, the more difficult it is to debug and maintain. 

Tools such as GhostQA minimize the efforts put behind scripting providing no-code possibilities allowing even non-technical users to write robust tests. 

6. Regularly Maintain Your Automation Suite 

Even though automation testing is a great way to ensure quality in applications, one of its biggest challenges is keeping the test scripts updated with application changes. Keeping your test suite effective and up to date, regular maintenance. 

Best practices for maintenance include: 

Frequent Reviews: Conduct periodic audit of the test scripts to ensure that they are not outdated. 

Version Control: Utilize version control systems to maintain history of your script modifications. 

Auto-Healing Features: GhostQA and similar tools can track UI updates and modify scripts to reflect changes with little to no human intervention, minimizing maintenance costs. 

Take good care of your automation suite so that it doesn't become a liability. 

7. Address Flaky Tests 

Flaky tests—tests that pass or fail randomly—are a common issue in automation testing. They reduce trust in test results and take up time when debugging. To address flaky tests: 

Dig deeper into what might be the underlying causes — timing problems or dynamic elements. 

Use explicit waits instead of static waiting in tests to make them aligned with application behavior. 

Prefer smart detection-based tools (GhostQA, to be precise) to eliminate the chances of flaky tests. 

This translates into flourish as flakiness and is the most significant impact in strengthening confidence in your automation framework. 

8. Ensure Cross-Browser and Cross-Platform Compatibility 

Most modern applications work across many browsers and devices, so cross-compatibility testing is a necessity. Your automation testing suite must: 

Add test cases for popular browsers like Chrome, Firefox, Edge, and Safari. 

Testing across different operating systems on mobile (e.g., iOS/Android). 

GhostQA abstracts cross-browser and cross-platform testing so you can verify functionality in several types of environments without repeating yourself. 

9. Leverage AI and Smart Automation 

AI is revolutionizing automation testing with better efficiency and lesser maintenance cost. Next-generation tools like GhostQA powered by AI offer: 

Auto-Healing: Automatically adjust to any changes made to the app;such as modified UI elements 

Predictive Analysis: Showcase areas with the most potential high risk to prioritize tests. 

Optimized Execution: Run just the tests that yield the most performance insights. 

Use AI-Powered Tools as these can help you to increase the efficiency and accuracy of your testing. 

10. Monitor and Measure Performance 

To measure the effectiveness of your automation testing, you should track key metrics that include: 

Test Coverage: Number of automated tests covering application features. 

Execution Time: Time taken to execute automated test suites. 

Defect Detection Rate: Number of bugs detected in automation testing 

Flaky Test Rate: Frequency of inconsistent test results. 

Consistent assessment of these metrics helps in discovering the areas of improvement in your automation efforts while also exhibiting the ROI of the same. 

Conclusion 

So, the right approach of selecting the right tool and plan properly will help to do a successful automation testing implementation. This could be achieved by adopting best practices like prioritizing test cases, maintaining test scripts, making use of the AI-powered tools and collaborating with other stakeholders in the process. 

Tools like GhostQA, which come equipped with codeless testing, auto-healing features, and user-friendly interfaces, empower teams of both technical and non-technical backgrounds to streamline their automation processes and devote their attention to shipping quality software. 

[thara333]

Pioneering the Future of Software Quality Assurance through Automation Testing

Automation testing, a dynamic and essential software quality assurance technique, is reshaping the landscape of application testing. Its mission is to execute predefined test cases on applications, delivering heightened accuracy, reliability, and efficiency by automating tedious and time-consuming testing tasks.

The Present and Future Synergy in Automation Testing:

At its essence, automation testing responds to the pressing need for a streamlined testing process. Beyond its current significance, the future promises a paradigm shift, characterized by transformative trends and advancements.

Unveiling Future Trends in Automation Testing:

Proactive "Shift-Left" Testing: Embracing a proactive "Shift-Left" approach, the future of automation testing integrates testing earlier in the development life cycle. This strategic shift aims to detect and address issues at their inception, fostering a more resilient and efficient software development process.

Harmonizing with DevOps: Automation is positioned to become increasingly integral to DevOps practices. Its seamless integration into continuous integration and delivery (CI/CD) pipelines ensures not just faster but more reliable releases, aligning seamlessly with the agile principles of DevOps.

AI and Machine Learning Synergy: The convergence of artificial intelligence (AI) and machine learning (ML) is poised to revolutionize automation testing. This integration enhances script maintenance, facilitates intelligent test case generation, and empowers predictive analysis based on historical data, ushering in a new era of adaptive and efficient testing processes.

Evolving Cross-Browser and Cross-Platform Testing: In response to the diversification of the software landscape, automation tools are evolving to provide robust solutions for cross-browser and cross-platform testing. Ensuring compatibility across diverse environments becomes paramount for delivering a seamless user experience.

Codeless Automation Revolution: The ascent of codeless automation tools represents a pivotal shift in testing methodologies. This trend simplifies testing processes, enabling testers with limited programming skills to create and execute automated tests. This democratization of testing accelerates adoption across teams, fostering a collaborative testing environment.

Concluding the Journey: Navigating Future Imperatives:

In conclusion, automation testing transcends its current role as a necessity, emerging as a future imperative in the ever-evolving landscape of software development. As technologies advance and methodologies mature, automation testing is poised to play a pivotal role in ensuring the delivery of high-quality software at an accelerated pace. Embracing these future trends, the software industry is set to embark on a transformative journey towards more efficient, adaptive, and reliable testing processes.

[cybersecurityict]

Automation Testing Market Size, Share, Analysis, Forecast, and Growth Trends to 2032: Software Quality Becomes a Strategic Priority

The Automation Testing Market was valued at USD 29.4 billion in 2023 and is expected to reach USD 118.6 billion by 2032, growing at a CAGR of 16.80% over 2024-2032.

The Automation Testing Market is experiencing a transformative shift as businesses increasingly prioritize faster time-to-market and enhanced software quality. Driven by the rising demand for digital transformation and agile methodologies, automation testing has become a critical element in software development lifecycles. Organizations are embracing automated solutions to minimize manual intervention, reduce errors, and ensure consistent performance across platforms.

Automation Testing Market continues to gain traction across sectors such as BFSI, healthcare, retail, telecom, and manufacturing. With the growing complexity of applications and integration of AI and machine learning into testing tools, the market is evolving rapidly. Enterprises are not just automating repetitive test cases but also leveraging intelligent automation to predict defects, improve test coverage, and enhance user experiences.

Get Sample Copy of This Report: https://www.snsinsider.com/sample-request/4127 

Market Keyplayers:

Selenium - Selenium WebDriver

Tricentis - Tosca

IBM - Rational Functional Tester

Micro Focus - UFT (Unified Functional Testing)

SmartBear - TestComplete

Cucumber - CucumberStudio

Appium - Appium

Katalon - Katalon Studio

Ranorex - Ranorex Studio

Worksoft - Worksoft Certify

Sahi - Sahi Pro

LambdaTest - LambdaTest

Eggplant - Eggplant Functional

Perfecto - Perfecto Test Automation

TestComplete - TestComplete

Telerik - Test Studio

Sauce Labs - Sauce Labs Selenium Grid

Applitools - Visual AI Testing

Postman - Postman API Testing

Tricentis – qTest

Market Analysis

The automation testing landscape is driven by rapid technological advancements and the increasing need for efficient, error-free deployment processes. Businesses are adopting DevOps and continuous integration/continuous deployment (CI/CD) pipelines, fueling the demand for scalable and flexible testing solutions. Cloud-based testing platforms and open-source tools have further expanded accessibility, enabling SMEs to compete alongside large enterprises. The growth of mobile and web applications has also intensified the requirement for robust cross-platform testing frameworks.

Market Trends

Rise of AI and Machine Learning: Intelligent automation is empowering predictive analytics in testing, enhancing accuracy and speed.

CI/CD Integration: Seamless integration of automation tools into CI/CD pipelines accelerates development cycles.

Cloud-Based Testing: Scalable cloud infrastructure enables remote and parallel testing environments.

Codeless Automation Tools: These tools are lowering the technical barriers, making automation accessible to non-developers.

Increased Adoption in SMEs: Open-source frameworks and SaaS models are driving adoption across small and medium businesses.

Market Scope

Expanding Across Verticals: Automation testing is being adopted in healthcare, eCommerce, BFSI, telecom, and automotive industries.

Global Penetration: North America leads, but Asia-Pacific is emerging rapidly with digitization initiatives.

Beyond Functional Testing: Growth in performance, security, and usability testing automation.

Support for Emerging Tech: Evolving tools support IoT, blockchain, and AR/VR applications.

High ROI Potential: Reduced human error, faster testing cycles, and better product quality.

As the demand for seamless user experiences and reliable digital platforms grows, the market's potential continues to expand. From startups to multinational corporations, the focus on automation is no longer optional but essential.

Market Forecast

The future of the Automation Testing Market is poised for exponential growth, powered by innovation and demand for faster, higher-quality releases. As enterprises transition from legacy testing methods to modern, AI-driven frameworks, automation is expected to redefine how software is built, tested, and delivered. With continuous investments in R&D and vendor competition heating up, the market is set to witness breakthroughs in intelligent test orchestration, self-healing scripts, and hyper-automation capabilities.

Access Complete Report: https://www.snsinsider.com/reports/automation-testing-market-4127 

Conclusion

In a world where digital agility defines success, the Automation Testing Market stands as a pivotal force in accelerating innovation. For businesses aiming to stay competitive, embracing automation isn't just a trend—it's a strategic imperative. Whether you're a tech leader, a QA professional, or an enterprise innovator, now is the time to capitalize on the wave of transformation driving this dynamic market forward.

About Us:

SNS Insider is one of the leading market research and consulting agencies that dominates the market research industry globally. Our company's aim is to give clients the knowledge they require in order to function in changing circumstances. In order to give you current, accurate market data, consumer insights, and opinions so that you can make decisions with confidence, we employ a variety of techniques, including surveys, video talks, and focus groups around the world.

Contact Us:

Jagney Dave - Vice President of Client Engagement

Phone: +1-315 636 4242 (US) | +44- 20 3290 5010 (UK)

[testrigtechnologies]

What is Codeless Automation and How its work?

As software development cycles grow faster and more continuous, testing needs to move at the same velocity. Traditional automation—powerful though it is—can become a bottleneck when only a small group of engineers can write and maintain test scripts. Enter codeless test automation, a modern answer to the challenge of scaling quality across teams without requiring everyone to write code.

But codeless is more than just a buzzword—done right, it’s a collaborative, intelligent, and scalable testing methodology that’s redefining how organizations approach QA.

What Is Codeless Test Automation?

Codeless test automation refers to the use of platforms and tools that allow testers to create, execute, and maintain automated tests without writing traditional programming code. Instead of scripting in languages like Java or Python, testers interact with:

Drag-and-drop interfaces

Pre-built test blocks or visual workflows

Natural language inputs or behavior-driven design formats (like Gherkin)

These tools abstract the code behind the scenes, allowing both technical and non-technical team members to contribute to the automation process.

Low-Code vs. No-Code vs. Codeless Automation: Understanding the Differences

Although often used interchangeably, these terms are not the same:

Low-Code Automation provides a blend—it offers visual interfaces but also allows code injections for complex conditions. Perfect for semi-technical testers who want both control and ease.

No-Code Automation eliminates code entirely. It's built for business users and testers with no programming background. Simplicity is the goal—but often at the cost of flexibility.

Codeless Automation, as a broader term, may incorporate both low-code and no-code options. It focuses on abstracting complexity while still offering enough control for power users when needed.

Read also: Best Automation Testing Tools

How Does Codeless Testing Work?

Let’s walk through how a modern codeless automation platform functions:

1. Test Creation

You begin by interacting with the application under test (AUT)—clicking, typing, or performing other actions. The tool records these actions and translates them into a structured test case. Some platforms also allow building tests visually—connecting steps like flowchart blocks or writing plain English test scenarios.

2. Object Recognition

Modern tools use AI-powered selectors or smart locators that adapt when UI elements change. This is crucial because flaky tests are often caused by fragile selectors.

3. Test Data Integration

Need to run the same test for different user types or datasets? Codeless tools can link to spreadsheets, databases, or data generators—without scripting loops or variables.

4. Execution & Scheduling

Tests can be executed locally, on the cloud, or across real devices and browsers. You can schedule them daily or hook them into CI/CD tools like Jenkins, GitHub Actions, or Azure DevOps.

5. Reporting & Analysis

Post-execution, you get visual dashboards, logs, screenshots, and detailed analytics. Some tools even auto-file bugs in Jira when a test fails.

Which Tests Are Best Suited for Codeless Automation?

Not every test type fits codeless automation. It shines in areas like:

• UI Regression Tests

When your product UI evolves frequently, regression test coverage can grow exponentially. Codeless tools make it easier to keep up without burning out your dev team.

• Smoke Tests

Want to validate login, dashboard loading, or payment gateway availability with every build? Codeless tools help you get quick feedback without writing dozens of scripts.

• End-to-End User Journeys

For tests that simulate real-world user paths—like signing up, purchasing a product, and logging out—codeless testing maps these flows efficiently and understandably.

• Cross-Browser / Device Testing

Codeless platforms often integrate with device farms (like BrowserStack or Sauce Labs), letting you run the same test across multiple environments without duplication.

When Not to Use Codeless Automation

Despite its power, codeless isn’t a silver bullet.

Highly complex workflows involving encrypted data, chained APIs, or backend validations still need traditional scripting.

Performance testing, load testing, and deep service-layer tests are beyond the reach of most codeless tools.

If your team needs 100% control over logic, libraries, and exceptions, coded automation is still king.

Final Thoughts

Codeless automation is about making test automation accessible, collaborative, and scalable. It’s not about replacing developers—it's about enabling QA teams to move faster and contribute earlier.

When adopted strategically, codeless testing can reduce time-to-market, increase test coverage, and empower entire teams to contribute to quality.

Want to Get Started With Codeless Automation?

At Testrig Technologies, As a leading Automation Testing Company, we specialize in integrating codeless tools into robust testing ecosystems—balancing ease with enterprise-grade power.

📩 Reach out for a free strategy session, and let’s build a smarter, faster, more inclusive QA process—together.

[govindhtech]

Terra Quantum Debuts Qode Engine And QAI Hub for QML

TQ42 Studio's Closed Beta: QAI Hub Makes Quantum AI Commonplace

On World Quantum Day, Rethinking Accessibility and Breaking Down Barriers with a No-Code Quantum ML Milestone

Terra Quantum launches TQ42 Studio Closed Beta on World Quantum Day. QAI Hub and Qode Engine make up this ecosystem, which aims to accelerate quantum AI deployment. QAI Hub, a no-code quantum machine learning platform, is the launch's centrepiece, even if Qode Engine (Python SDK) allows advanced developers.

Importance of Quantum AI

Quantum AI might revolutionise supply chain optimisation and industrial forecasting, but most teams cannot afford it. Specialised expertise and high coding requirements delay adoption. Terra Quantum and TQ42 Studio want to foster quantum AI innovation:

Increase Model Generalisation

Quantum neural networks may catch subtle data patterns, making models more responsive to real-world complexity.

Encode Richer Exponential Data

Quantum states' exponential data encoding allows higher-dimensional exploration without exponential processing expenses.

Smaller Datasets Deepen Understanding

Hybrid quantum-classical layers can quickly uncover patterns with less data, which is important for R&D.

Make More Reliable Predictions

Quantum machine learning (ML) can increase prediction accuracy from near-real-time optimisation to sophisticated forecasting.

Terra Quantum created the QAI Hub in TQ42 Studio to make experiment-driven R&D safer, upskill teams faster with (changing) TQ Academy courses, and boost accessibility.

Beta version of QAI Hub: Quantum Machine Learning Without Code

QAI Hub, Terra Quantum's no-code platform, simplifies quantum-enhanced AI prototyping. Teams who wish to analyse ideas and build quantum skills without complex programming will love it. QAI Hub cherishes your comments as it develops to make quantum AI open to anyone in beta.

Beta test the QAI Hub.

Accessible quantum ML

Creating hybrid quantum-classical models is easy without quantum expertise. employ QAI Hub's TQml tools to employ our powerful Hybrid Quantum Neural Networks.

Codeless Model Builder

Use of quantum neural networks has never been so easy! You can build and train a QML model in 5 visual steps without coding, starting with automated data processing.

Flexibility of Hybrid Computing

Try quantum machine learning with HPC (CPUs, GPUs) and QPU access. This method is good for concept validation and prototyping.

Agentic AI Help

As your conversational AI helper, TQ Copilot tackles laborious model design and tuning. Let TQai manage quantum neural networks while you focus on your goals.

Integration with TQ Academy

Early access to Terra Quantum's professionals' learning resources; more in-depth courses to follow.

How does QAI Hub work?

Five easy steps to construct, adjust, and run quantum machine learning models:

Import and prepare data safely with automated tools.

Create quantum-classical models with the visual interface with TQ Copilot.

Your models will perform seamlessly on CPUs, GPUs, and QPUs.

Evaluation & Optimisation: Improve models with automated hyperparameter tweaking and advanced evaluation tools.

Prediction and Scaling: Make accurate projections and scale your successful trials to corporate deployments.

The Promise of Quantum AI

Increase model generalisation

Encode richer data.

Gain deeper insight from small datasets

Make more reliable forecasts.

Python SDK Improves Qode Engine Developer Control

Qode Engine provides developers and data scientists with a sophisticated Python SDK for quantum-enhanced corporate infrastructures. Even in beta, Qode Engine's infrastructure may develop from prototypes to production-grade solutions.

Benefits of Qode Engine

Advanced Quantum Algorithms

optimisation: Solve difficult optimisation issues with TetraOpt, TQoptimaX, ClearVu Analytics, QuEnc, and TQrouting.

TQml improves analytical depth and prediction accuracy.

Solid Python SDKs/APIs

Documentation and APIs simplify quantum model building.

Improve quantum models and integrate them into your Python routine quickly.

Hybrid, adaptable implementation

Mix CPUs, GPUs, and (eventually) Quantum Processing Units for best performance and cost.

Coordination with your existing infrastructure allows easy on-premises or cloud deployment (AWS, Azure, Google Cloud).

Framework Development for Security and Compliance

Due to its enterprise-grade architecture, Qode Engine meets security standards.

OIDC/OAuth2 authentication is supported by customisable RBAC and ReBAC.

Which SDK Libraries Exist?

The Qode Engine Python SDK supports TetraOpt, TQoptimaX, ClearVu Analytics, QuEnc, TQrouting, and TQml algorithms for optimisation and quantum machine learning.

Qode Engine works how?

Developers and data scientists may easily integrate quantum-enhanced activities into company infrastructures using a sophisticated Python SDK.

The normal Qode Engine process includes these steps:

Users can manually prepare or obtain data from their systems through data intake.

Model Development: The Python SDK designs, tests, and optimises quantum machine learning and optimisation workflows.

Solutions are performed using HPC resources such CPUs and GPUs, with some QPUs added later.

[aisoftwaretesting]

Testing for Super Apps: New QA Strategies for Multi-Functional Platforms

Modernizing QA with Genqe.ai AI-Powered Testing

Super Apps — integrated platforms that combine services like payments, messaging, e-commerce, booking, and social engagement — have redefined the digital experience. With high complexity and immense user expectations, these apps demand a reimagined QA strategy to ensure quality, reliability, and rapid delivery.

In 2025, the key to success lies in intelligent, scalable, and codeless automation — and that’s exactly what Genqe.ai delivers.

The QA Challenge of Super Apps

Super Apps are not typical mobile apps. They’re multi-service ecosystems with features spanning across:

Financial transactions

Social media integrations

Real-time chat

On-demand services

Loyalty and rewards programs

This complexity introduces challenges such as:

Interdependent module testing

Continuous regression across frequently updated components

UI consistency across devices and brands

High-volume test coverage with limited time

Genqe.ai: Your Smart QA Co-Pilot for Super Apps

Genqe.ai is an AI-powered, codeless test automation platform designed to keep up with the ever-evolving architecture of Super Apps. Here’s how it transforms QA strategy:

AI-Powered Test Case Generation

Genqe.ai AI analyzes application flows and auto-generates test cases for even the most complex journeys. For a super app, this includes:

User onboarding across modules

Cross-feature transaction testing (e.g., booking and payment)

Context-aware journeys like “Chat while ordering”

It continuously updates test cases as the app evolves — no manual intervention required.

Unified Functional & Visual Testing

Super Apps must function seamlessly and look consistent across screen sizes, languages, and user types. Genqe.ai combines functional and AI-driven visual testing to:

Validate core logic and UI integrity together

Detect pixel-level mismatches

Ensure responsiveness across OS and device variants

The result: a cohesive user experience across all modules.

Scalable Cross-Module Regression Testing

With Genqe.ai, teams can execute parallel tests across integrated modules and services, ensuring that updates in one area don’t break another. This is critical for:

Shared authentication systems

Centralized wallets used across services

Notifications that trigger in multiple flows

Regression testing becomes smarter, faster, and fully autonomous.

API + Microfrontend Testing in One Flow

Super Apps are powered by complex APIs and sometimes microfrontend frameworks. Genqe.ai supports:

API testing directly within the same test scenarios

Seamless validation of data exchanges across microservices

Contract testing for service agreements

This ensures robust integrations behind the scenes — without separate test suites.

Real-Time Dashboards & Smart Reporting

Genqe.ai brings transparency to test execution with intuitive dashboards. QA leaders gain:

Instant visibility into test health across modules

Smart prioritization of failed tests

Heatmaps showing defect density across app areas

This data-driven insight accelerates quality decision-making.

Real-World Use Case: One Super App, Many Journeys

Imagine a user browsing products, making a payment, chatting with support, and booking a delivery — all in one session.

With Genqe.ai, QA teams can build and validate this entire experience as a single flow, fully automated and self-healing across environments.

Conclusion: QA for Super Apps Starts with Smart Automation

Super Apps demand next-generation QA tools — and Genqe.ai delivers the speed, scalability, and intelligence needed to support multi-functional platforms. With codeless automation, adaptive test generation, and deep integration support, Genqe.ai helps teams test faster, smarter, and more reliably in 2025.

[assureqa-ai]

What are the best automation tools for software testing?

​In the rapidly evolving landscape of software testing, selecting the right automation tools is crucial for ensuring efficiency and accuracy. As of 2025, several tools have distinguished themselves in the field:​

1. Selenium

Selenium remains a leading open-source framework for web application testing. It supports multiple programming languages and is compatible across various browsers and operating systems, making it a versatile choice for developers. ​

2. Cypress

Cypress is renowned for its end-to-end testing capabilities, particularly for modern web applications. It offers real-time testing and a developer-friendly experience, streamlining the testing process. ​

3. Appium

For mobile application testing, Appium provides a robust open-source framework that supports both iOS and Android platforms. Its cross-platform capabilities allow testers to write tests against multiple mobile platforms using the same API. ​

4. ACCELQ

ACCELQ is an AI-powered, codeless test automation platform that enables testing across API, web, mobile, and desktop applications. It emphasizes seamless integration into Agile and DevOps environments, facilitating continuous testing. ​

5. AssureQA

AssureQA stands out as a comprehensive, AI-driven, no-code platform designed to streamline testing workflows. It offers capabilities for web, API, mobile, and visual testing, featuring self-healing tests, analytics for performance optimization, and seamless integration with CI/CD tools. AssureQA is the ultimate destination for software testing tools in 2025, providing scalable solutions to meet diverse testing needs.

Selecting the appropriate tool depends on specific project requirements, including the application type, development environment, and team expertise. Evaluating these factors will help in choosing the most suitable automation tool to enhance testing efficiency and software quality.

[differenttimemachinecrusade]

Crowdsourced Testing Market Overview: Key Innovations and Future Trends 2032

Crowdsourced Testing Market size was valued at USD 2.6 Billion in 2023 and is expected to reach USD 6.3 Billion by 2032, growing at a CAGR of 10.4% over the forecast period 2024-2032

Crowdsourced Testing Market is rapidly transforming the software quality assurance landscape, offering cost-effective, scalable, and real-world testing solutions. Companies are increasingly leveraging global testers to ensure high-quality digital experiences. The market is experiencing significant growth as demand for faster and more efficient testing methods rises.

Crowdsourced Testing Market continues to gain momentum due to the growing complexity of software applications and the need for extensive testing across multiple devices, platforms, and geographies. Businesses are adopting this model to accelerate testing cycles, enhance test coverage, and obtain diverse user insights, making it a preferred choice for modern software development.

Get Sample Copy of This Report: https://www.snsinsider.com/sample-request/3680 

Market Keyplayers:

Applause (Applause Platform, Applause Codeless Automation)

uTest (uTest Platform, Test Cycle Management)

Testlio (Testlio Platform, Testlio Managed Testing)

Crowdtest (Crowdtest Dashboard, Bug Discovery Service)

Passbrains (Passbrains Platform, Passbrains Marketplace)

Bugcrowd (Bug Bounty Program, Vulnerability Disclosure Program)

Synack (Synack Red Team, Synack Vulnerability Intelligence)

Global App Testing (Functional Testing, Exploratory Testing)

Rainforest QA (Rainforest Automation, Rainforest Tester Network)

Cobalt (Cobalt Pentest Platform, Cobalt Core)

99tests (Crowd Testing Platform, Functional Testing Suite)

Testbirds (Testbirds Nest, Device Cloud)

Digivante (Digivante Platform, Exploratory Testing)

Crowdsprint (Crowdsprint Testing Services, Performance Testing)

test IO (Exploratory Testing, test IO Automation)

QaizenX (Crowdtesting Platform, App Usability Testing)

Mob4Hire (MobTest Platform, Crowdsource Usability Testing)

Crowd4Test (Crowd4Test Platform, Mobile App Testing)

WeAreTesters (Crowdsourced QA, Bug Bounty Services)

Market Trends Driving Growth

1. Rising Demand for Agile and DevOps Testing

Organizations are shifting towards Agile and DevOps methodologies, increasing the need for continuous testing. Crowdsourced testing aligns well with these approaches, enabling rapid feedback and seamless integration into the software development lifecycle.

2. Increased Mobile and IoT Testing Needs

With the proliferation of mobile applications and Internet of Things (IoT) devices, companies require testing across a wide range of real-world environments. Crowdsourced testing provides access to diverse testers, ensuring comprehensive device and network compatibility testing.

3. AI-Driven Test Automation and Crowdsourcing

The integration of Artificial Intelligence (AI) and Machine Learning (ML) is enhancing test automation, making crowdsourced testing more efficient. AI-powered test execution, defect prediction, and automated test case generation are streamlining the process.

4. Cost-Effective and Scalable Testing Solutions

Companies are turning to crowdsourced testing to reduce operational costs while scaling their testing efforts. This approach eliminates the need for expensive in-house testing teams and infrastructure, offering flexibility based on project requirements.

5. Security and Compliance Testing in Focus

With growing concerns around cybersecurity and regulatory compliance, businesses are leveraging ethical hackers and security testers from crowdsourced platforms to identify vulnerabilities and ensure data protection.

Enquiry of This Report: https://www.snsinsider.com/enquiry/3680 

Market Segmentation:

By Component

Platform

Service

By Testing Type

Exploratory Testing                       

Graphical User Interface (GUI) Testing

Usability Testing                

Functional Testing             

Performance Testing                     

Others           

By Application

Mobile Applications                       

Web Applications                

Native Desktop Applications

By Organization Size

Small And Medium Sized Enterprises (SMEs)

Large Size Enterprises

By Industry

BFSI              

Retail            

IT & Telecom                       

Media & Entertainment                

Healthcare               

Market Analysis and Growth Potential

Key drivers include:

Expansion of digital transformation initiatives across industries.

Rising adoption of AI and automation tools in software testing.

Growing demand for real-time feedback from end users.

Increase in remote work and global collaboration enabling better access to global tester networks.

Despite its rapid expansion, the market faces challenges such as test result validation, security concerns, and maintaining consistent tester quality. However, advancements in AI-driven test management and automation are addressing these issues.

Regional Analysis: Global Market Trends

North America

North America dominates the crowdsourced testing market due to the presence of major technology firms, high adoption of DevOps practices, and the increasing demand for digital transformation. The U.S. leads the region with strong investments in AI-driven testing solutions.

Europe

Europe is witnessing significant growth in crowdsourced testing, driven by regulatory requirements such as GDPR and the need for secure, compliant software solutions. The increasing adoption of mobile apps and fintech solutions is further boosting demand.

Asia-Pacific

Asia-Pacific is the fastest-growing region, fueled by the rise of e-commerce, mobile banking, and smart devices. Countries like India and China are becoming key players due to their vast talent pool of skilled testers and growing IT industry.

Rest of the World

Latin America and the Middle East are also seeing increased adoption, particularly in sectors like healthcare, fintech, and telecom, where quality assurance is critical for business success.

Future Prospects: Innovations and Market Expansion

1. AI-Powered Crowdsourced Testing

AI and ML will continue to enhance crowdsourced testing by automating test case selection, bug detection, and predictive analytics for faster and more accurate testing outcomes.

2. Blockchain for Secure Testing

The use of blockchain in crowdsourced testing is expected to improve data security, authentication of testers, and transparency in test result verification.

3. Growth of Niche and Specialized Testing

With increasing cybersecurity threats and regulatory requirements, demand for specialized testing services such as penetration testing, accessibility testing, and compliance testing will rise.

4. Expansion into Emerging Markets

The market will continue expanding into emerging economies, offering businesses access to a diverse pool of global testers and reducing costs while improving software quality.

5. Integration with Cloud-Based Testing Platforms

Cloud-based testing will further enhance the scalability and accessibility of crowdsourced testing, allowing seamless remote collaboration across different geographical locations.

Access Complete Report: https://www.snsinsider.com/reports/crowdsourced-testing-market-3680 

Conclusion

The crowdsourced testing market is experiencing rapid growth, driven by the increasing demand for scalable, cost-effective, and real-world software testing solutions. As organizations continue to embrace digital transformation, AI-powered automation, and global tester networks, the market is set for significant expansion. With continuous innovations in testing methodologies, security measures, and AI-driven analytics, crowdsourced testing will play a pivotal role in shaping the future of software quality assurance.

About Us:

SNS Insider is one of the leading market research and consulting agencies that dominates the market research industry globally. Our company's aim is to give clients the knowledge they require in order to function in changing circumstances. In order to give you current, accurate market data, consumer insights, and opinions so that you can make decisions with confidence, we employ a variety of techniques, including surveys, video talks, and focus groups around the world.

Contact Us:

Jagney Dave - Vice President of Client Engagement

Phone: +1-315 636 4242 (US) | +44- 20 3290 5010 (UK)

[yethiconsulting]

Best Practices for Test Management in a Continuous Integration/Delivery (CI/CD) Environment

Introduction

Start by explaining the role of Continuous Integration (CI) and Continuous Delivery (CD) in modern software development. Emphasize that effective test management is crucial to maintaining quality in fast-paced, automated pipelines.

Early and Continuous Testing

Implement testing at every stage of the CI/CD pipeline, starting from the earliest phases. Unit, integration, and functional tests should be run continuously to catch defects early.

Automation Integration

Test automation is vital for CI/CD environments. Ensure that all repetitive tests, such as regression tests, are automated. Use tools like Selenium, Jenkins, and Travis CI to integrate automated tests into the pipeline.

Effective Test Case Management

Organize test cases in a way that they can be easily maintained and executed in CI/CD pipelines. Regularly review and update test cases to ensure they are relevant and up-to-date.

Use of Test Management Tools

Leverage test management tools like TestRail or Zephyr that integrate with CI/CD platforms. This ensures seamless tracking, reporting, and scheduling of tests within the automated process.

Monitoring and Reporting

Set up real-time monitoring and reporting for continuous feedback on test results. This helps in quickly identifying issues and improving collaboration between developers and QA teams.

Conclusion

Summarize by stating that efficient test management in a CI/CD environment enhances the speed and reliability of software delivery while maintaining high-quality standards.

[tosca-automation-training]

Boost Your Career with Tricentis TOSCA Certification: A Step-by-Step Guide

Introduction

In today’s fast-paced world of software testing, automation has become a crucial component of delivering high-quality applications efficiently. One of the most powerful automation tools in the market is Tricentis TOSCA, which enables businesses to streamline their testing processes and reduce time-to-market. With companies increasingly adopting automation testing, obtaining a Tricentis TOSCA Certification can set you apart in the competitive job market.

If you’re a software tester looking to advance your career, learning Testing Tool TOSCA through structured TOSCA Training Online is a great step. Certification in TOSCA validates your skills and expertise, making you a valuable asset to organizations seeking automation professionals. This blog will guide you through everything you need to know about Tricentis TOSCA Certification, how to get certified, and how it can enhance your career prospects.

What is Tricentis TOSCA?

Overview of TOSCA Automation Tool

Tricentis TOSCA is a continuous testing platform that supports automated, codeless, and AI-driven testing across multiple technologies, including web, mobile, APIs, and enterprise applications. It follows a model-based testing approach, allowing testers to create, execute, and manage test cases efficiently.

Why is TOSCA Popular?

TOSCA stands out among automation tools because of its low-code/no-code functionality, making it accessible to both beginners and experienced testers. Its key features include:

Model-Based Test Automation – Simplifies test creation and maintenance.

Scriptless Test Automation – Reduces manual effort and increases test coverage.

End-to-End Testing – Supports multiple platforms, including SAP, Salesforce, and mobile apps.

AI-Powered Test Execution – Enhances test efficiency with machine learning capabilities.

Risk-Based Testing – Prioritizes test cases based on business risk.

Integration with CI/CD Pipelines – Supports DevOps environments.

TOSCA is widely used in industries such as banking, healthcare, retail, and telecommunications, making it a valuable skill for testers.

Why Get Tricentis TOSCA Certified?

A Tricentis TOSCA Certification validates your skills in using the automation tool, making you a sought-after professional in the testing industry. Here are the key reasons to get certified:

1. High Demand for TOSCA Professionals

With the increasing adoption of test automation, TOSCA experts are in high demand. Companies using Agile and DevOps methodologies require skilled automation testers to optimize their testing strategies.

2. Career Growth and Higher Salary

According to industry reports, certified TOSCA professionals earn higher salaries compared to manual testers. On average, an automation tester with TOSCA skills can earn between $80,000 to $120,000 per year, depending on experience and location.

3. Job Opportunities Across Industries

TOSCA-certified professionals can work in diverse industries, including:

Finance & Banking – Automating financial applications for faster transactions.

Healthcare – Ensuring medical applications meet compliance standards.

Retail & E-commerce – Testing online platforms for seamless user experience.

Telecommunications – Validating complex telecom networks.

4. Competitive Advantage

A TOSCA certification gives you an edge over non-certified candidates when applying for QA Engineer, Test Automation Engineer, and Software Tester roles.

5. Improved Test Automation Skills

Certification enhances your ability to implement automation strategies, improving efficiency and reducing manual testing efforts.

Types of Tricentis TOSCA Certifications

Tricentis offers various certifications, each catering to different levels of expertise. Below are the most recognized certifications:

1. Tricentis Certified Automation Specialist Level 1 & 2

Ideal for beginners.

Covers fundamental and intermediate automation concepts.

Includes hands-on exercises and scenario-based test automation.

2. Tricentis Certified Test Automation Engineer

Advanced certification for professionals with experience in automation.

Covers CI/CD integration, API testing, and advanced scripting techniques.

3. Tricentis Certified Test Architect

For experienced testers looking to design and implement automation frameworks.

Focuses on enterprise-level automation strategies.

4. Tricentis Certified DevOps Practitioner

Targets professionals integrating TOSCA in DevOps pipelines.

Covers continuous testing and deployment strategies.

5. Tricentis Certified Performance Engineer

Focuses on performance testing and optimizing test execution speed.

Each certification provides official recognition from Tricentis, enhancing your credibility as an automation expert.

How to Get Tricentis TOSCA Certified?

To obtain a Tricentis TOSCA Certification, follow these steps:

Step 1: Enroll in TOSCA Training Online

The first step is to complete a TOSCA Training Online course. Many training providers offer self-paced and instructor-led programs that cover:

TOSCA Basics & Installation

Test Case Design & Execution

Modules & Test Data Management

API Testing

CI/CD Pipeline Integration

Step 2: Gain Hands-On Experience

Practicing in a real-world testing environment is essential. You can:

Download Tricentis TOSCA Trial Version to practice test creation.

Work on automation projects in a sandbox environment.

Participate in online TOSCA communities to learn best practices.

Step 3: Register for the Certification Exam

Visit the Tricentis Academy website.

Choose the certification that matches your expertise.

Pay the exam fee (varies based on certification level).

Schedule your exam online.

Step 4: Take the Exam

The certification exam typically includes:

Multiple-choice questions covering theoretical concepts.

Practical assessments where you automate real-world scenarios using TOSCA.

Step 5: Get Certified and Apply Your Skills

After passing the exam, you will receive an official Tricentis certification. You can now showcase your certification on LinkedIn, resumes, and job applications to attract employers.

Real-World Applications of TOSCA Automation

To understand the impact of TOSCA, let’s explore some real-world use cases:

1. Banking Sector

A leading global bank implemented TOSCA to automate end-to-end transactions, reducing test execution time by 60% and minimizing human errors.

2. Healthcare Industry

A healthcare provider used TOSCA for regression testing of electronic health records (EHR), ensuring compliance with HIPAA regulations.

3. Retail & E-commerce

An e-commerce giant integrated TOSCA into its CI/CD pipeline, enabling faster deployments with automated checkout and payment process testing.

These case studies highlight how Testing Tool TOSCA improves efficiency and software quality across different industries.

Tips to Succeed in the TOSCA Certification Exam

To pass the TOSCA certification exam, follow these best practices:

✅ Understand Core Concepts

Learn model-based testing principles.

Understand test case design, execution, and reporting.

✅ Practice Hands-On Scenarios

Create automation scripts for web, mobile, and API testing.

Work on real-world projects to gain practical exposure.

✅ Join Online Communities

Engage with Tricentis forums, LinkedIn groups, and Slack communities.

Discuss challenges and solutions with experienced professionals.

✅ Use Official Study Materials

Access Tricentis Academy resources.

Review sample exam questions and mock tests.

Conclusion

Getting Tricentis TOSCA Certification is a game-changer for professionals aiming to excel in test automation. As businesses continue to adopt automation testing, Testing Tool TOSCA expertise is becoming a must-have skill. Enrolling in TOSCA Training Online equips you with practical knowledge to pass the certification and secure high-paying job opportunities.

Take the next step in your automation journey by enrolling in a TOSCA training program today and unlocking new career opportunities!

Ready to level up your skills? Dive into our ultimate resource: TOSCA Automation Tool: A Complete Guide.

[ideyalabsllp]

Are You Ready for the AI-Powered Future? QA Consulting in 2025

QA Consulting in 2025: Are You Ready for the AI-Powered Future?

The landscape of software testing is evolving at an unprecedented pace. With artificial intelligence (AI), cloud-based testing, and automation taking center stage, traditional quality assurance (QA) methods are becoming obsolete. QA consulting companies are at the forefront of this transformation, helping businesses adapt and optimize their testing strategies for the future. As we approach 2025, it is crucial for QA managers, decision-makers, and project managers to assess whether their QA strategies are equipped to handle the challenges of an AI-driven future.

The Role of QA Consulting Companies in the AI Era

1. AI-Driven Test Automation

AI-powered test automation is revolutionizing how software is tested. Traditional testing methods, which relied heavily on manual efforts, are giving way to intelligent automation frameworks. QA consulting companies are integrating AI-based solutions to enhance test coverage, reduce human error, and speed up release cycles.

2. Predictive Analytics for Better Decision-Making

By leveraging machine learning algorithms, QA consulting companies can predict potential software failures before they occur. This predictive approach helps organizations preemptively address quality issues, leading to more stable and reliable software products.

3. Cloud-Based Testing for Scalability

Cloud technology is reshaping software testing by offering scalable and flexible environments. QA consulting companies provide expertise in implementing cloud-based testing solutions that enable businesses to perform large-scale, distributed testing without infrastructure limitations.

Key Trends Shaping Software Testing in 2025

AI-Powered Test Case Generation

AI-driven tools are now capable of generating test cases automatically based on historical data and user interactions. This reduces the burden on QA teams while improving efficiency and accuracy.

Shift-Left Testing Approach

The shift-left methodology emphasizes testing early in the development lifecycle, preventing defects rather than detecting them later. QA consulting companies are guiding organizations in implementing this proactive approach, ensuring software quality from the outset.

Codeless Test Automation

With the rise of no-code and low-code platforms, test automation is becoming more accessible. QA consulting companies are helping businesses adopt codeless automation tools, enabling non-technical testers to contribute to software quality assurance.

The Business Impact of AI-Driven QA Consulting

Cost Efficiency and Faster Time-to-Market

By leveraging AI and automation, QA consulting companies help businesses cut down testing costs and accelerate software delivery. Automated test execution reduces manual effort, allowing teams to focus on strategic testing initiatives.

Enhanced Software Security

As cyber threats become more sophisticated, security testing is paramount. QA consulting companies incorporate AI-driven security testing to detect vulnerabilities in real-time, ensuring software integrity and user trust.

Seamless Integration with DevOps

AI-powered QA solutions seamlessly integrate with DevOps pipelines, enabling continuous testing and delivery. This ensures that quality is maintained throughout the software development lifecycle without causing delays.

Are You Ready for the AI-Powered Future?

The future of software testing is intelligent, predictive, and automated. QA consulting companies play a crucial role in helping organizations navigate this evolving landscape. By embracing AI-driven testing solutions, predictive analytics, and cloud-based strategies, businesses can stay ahead of the curve and deliver high-quality software products.

Conclusion & Call to Action

If your QA strategy is still relying on outdated methods, now is the time to make the shift. QA consulting companies provide the expertise needed to future-proof your testing processes and ensure long-term success in an AI-powered world.

Are you ready to elevate your software quality with AI-driven QA consulting? Contact us today to explore cutting-edge solutions tailored to your business needs.

[thara333]

Charting the Course for Tomorrow's Testing Revolution: A Glimpse into the Future of Test Automation

In the ever-shifting landscape of software testing, the future is on the brink of a transformative revolution, driven by technological innovations and paradigm shifts. As we peer into the horizon of test automation, a realm of exciting developments unfolds, promising a testing landscape where adaptability and innovation take center stage.

1. The Rise of Smart Testing with AI and Machine Learning: The integration of Artificial Intelligence (AI) and Machine Learning (ML) into test automation marks a paradigm shift. Testing tools, infused with intelligence, will evolve to dynamically adapt, optimize scripts, and autonomously discern patterns. The era of intelligent and responsive test automation is on the horizon.

2. Embracing Shift-Left Testing Practices: The industry's commitment to a shift-left approach continues to gain momentum. Test automation seamlessly integrates into CI/CD pipelines, fostering swift feedback loops and hastening release cycles. Early testing in the development lifecycle transforms from a best practice into a fundamental aspect of agile methodologies.

3. Codeless Testing: Empowering Beyond Boundaries: Codeless testing tools take center stage, breaking down barriers and democratizing the testing process. Individuals with diverse technical backgrounds can actively contribute, fostering collaboration among developers, testers, and business stakeholders. The inclusivity of codeless testing reshapes the collaborative dynamics of testing efforts.

4. Navigating Production Realms with Shift-Right and Chaos Engineering: Test automation extends beyond development environments with a pronounced shift-right approach. Venturing into production environments, automation tools provide real-time insights, ensuring application reliability in live scenarios. Simultaneously, Chaos Engineering emerges as a pivotal practice, stress-testing system resiliency.

5. Unveiling Advanced Test Reporting and Analytics: Test automation tools evolve beyond mere script execution, offering enhanced reporting and advanced analytics. Deep insights into testing trends empower teams with actionable data, enriching decision-making processes and optimizing the overall testing lifecycle.

6. IoT and Mobile Testing Evolution: With the pervasive growth of the Internet of Things (IoT) and mobile applications, test automation frameworks adapt to meet the diverse testing needs of these platforms. Seamless integration with mobile and IoT devices becomes imperative, ensuring comprehensive test coverage across a spectrum of devices.

7. Hyper-Automation and Seamless Connectivity: The concept of hyper-automation takes center stage, amalgamating multiple automation technologies for advanced testing practices. Automation tools seamlessly connect with diverse ecosystems, creating a hyper-connected testing landscape. This interconnectedness ushers in a holistic approach, addressing the intricacies of modern software development.

8. The Imperative of Continuous Reskilling and Upskilling: Testers of the future embrace a culture of continuous learning. Proficiency in scripting languages, understanding AI and ML concepts, and staying updated with the latest testing methodologies become imperative. The ability to adapt and upskill becomes the linchpin of a successful testing career.

In conclusion, the future of test automation unveils a dynamic and revolutionary journey. Testers and organizations at the forefront of embracing emerging technologies and agile methodologies will not only navigate but thrive in this evolving landscape. As the synergy between human expertise and automation technologies deepens, the future promises to unlock unprecedented possibilities in the realm of software quality assurance.

[cybersecurityict]

Crowdsourced Testing Market Size, Share, Analysis, Forecast, Growth 2032: Consumer Behavior and Market Demand Analysis

Crowdsourced Testing Market size was valued at USD 2.6 Billion in 2023 and is expected to reach USD 6.3 Billion by 2032, growing at a CAGR of 10.4% over the forecast period 2024-2032.

Crowdsourced Testing Market is rapidly transforming the software quality assurance landscape, driven by the rising need for agile, cost-effective, and real-time testing solutions. This approach leverages a global pool of testers to evaluate digital products under real-world conditions, enabling companies to deliver superior user experiences. From startups to large enterprises, organizations are embracing crowdsourced testing to shorten release cycles and identify critical bugs across a wider range of devices, networks, and geographies.

Crowdsourced Testing Market is witnessing robust traction as businesses seek to enhance product reliability while maintaining speed-to-market. The availability of diverse testers helps uncover usability issues and functional defects early, reducing the cost and time of post-release fixes. This decentralized testing model also complements DevOps practices by providing continuous feedback through parallel testing, thus improving test coverage and scalability.

Get Sample Copy of This Report: https://www.snsinsider.com/sample-request/3680 

Market Keyplayers:

Applause (Applause Platform, Applause Codeless Automation)

uTest (uTest Platform, Test Cycle Management)

Testlio (Testlio Platform, Testlio Managed Testing)

Crowdtest (Crowdtest Dashboard, Bug Discovery Service)

Passbrains (Passbrains Platform, Passbrains Marketplace)

Bugcrowd (Bug Bounty Program, Vulnerability Disclosure Program)

Synack (Synack Red Team, Synack Vulnerability Intelligence)

Global App Testing (Functional Testing, Exploratory Testing)

Rainforest QA (Rainforest Automation, Rainforest Tester Network)

Cobalt (Cobalt Pentest Platform, Cobalt Core)

99tests (Crowd Testing Platform, Functional Testing Suite)

Testbirds (Testbirds Nest, Device Cloud)

Digivante (Digivante Platform, Exploratory Testing)

Crowdsprint (Crowdsprint Testing Services, Performance Testing)

test IO (Exploratory Testing, test IO Automation)

QaizenX (Crowdtesting Platform, App Usability Testing)

Mob4Hire (MobTest Platform, Crowdsource Usability Testing)

Crowd4Test (Crowd4Test Platform, Mobile App Testing)

WeAreTesters (Crowdsourced QA, Bug Bounty Services)

Market Analysis

The crowdsourced testing market is shaped by the evolving demands of the digital economy. Companies are increasingly recognizing the limitations of traditional testing environments, particularly when it comes to testing under diverse real-world conditions. Crowdsourced testing platforms offer flexibility, global tester reach, and faster execution, making them ideal for mobile apps, web platforms, gaming, IoT, and other digital products. The surge in smartphone penetration, expansion of internet services, and growing complexity of applications are further fueling the adoption of this model.

Additionally, the market is being driven by increasing focus on user experience, where usability and accessibility play critical roles. Organizations are also turning to crowdsourced testing to ensure compliance with localization standards and diverse user demographics.

Market Trends

Increased adoption among SMEs: Small and medium enterprises are leveraging crowdsourced testing for its cost-efficiency and access to global testers without infrastructure investments.

Integration with AI and automation tools: Crowdsourced platforms are enhancing their capabilities by incorporating AI-driven insights and automation features for smarter test management.

Focus on cybersecurity testing: With rising threats, companies are increasingly using ethical hackers and testers in crowdsourced environments to identify security vulnerabilities.

Greater use in localization testing: Brands expanding globally are using crowd testers to ensure cultural, linguistic, and functional alignment across regions.

Real-time testing demand: As development cycles shorten, the need for on-demand, real-time testing is growing, making crowdsourced testing a strategic fit for agile and DevOps methodologies.

Market Scope

The crowdsourced testing market spans across various sectors including e-commerce, BFSI, healthcare, telecommunications, gaming, and media & entertainment. Its scope extends beyond simple bug detection to encompass exploratory testing, usability feedback, beta testing, localization validation, and performance testing. The ability to conduct tests across different geographies, devices, browsers, and network conditions gives this market a significant edge over conventional QA methods.

Furthermore, as digital transformation initiatives accelerate globally, the demand for scalable, diverse, and real-world testing environments is becoming indispensable. Crowdsourced testing not only offers scalability but also helps companies validate their digital products under diverse environmental factors that in-house testing teams may not replicate efficiently.

Market Forecast

The future of the crowdsourced testing market is highly promising, supported by increasing digital product rollouts and the evolution of cloud-based testing infrastructure. As enterprises continue to prioritize user satisfaction and rapid deployment cycles, crowdsourced testing will become a cornerstone of software quality assurance strategies. Expansion in emerging economies, rise in remote work models, and growing reliance on mobile-first applications are expected to drive further market penetration.

Market players are likely to focus on strategic partnerships, AI integration, and tester community development to expand their offerings. The growth trajectory is further strengthened by regulatory requirements for accessibility, performance benchmarks, and the growing complexity of user behavior across different platforms.

Access Complete Report: https://www.snsinsider.com/reports/crowdsourced-testing-market-3680 

Conclusion

In an era where digital experience defines brand perception, crowdsourced testing emerges as a vital enabler of quality and agility. Its ability to tap into global user insights and provide scalable, real-world testing makes it a game-changer for businesses aiming to deliver flawless digital interactions. As technology evolves, those who strategically harness the power of the crowd will lead with innovation, user satisfaction, and competitive advantage.

About Us:

SNS Insider is one of the leading market research and consulting agencies that dominates the market research industry globally. Our company's aim is to give clients the knowledge they require in order to function in changing circumstances. In order to give you current, accurate market data, consumer insights, and opinions so that you can make decisions with confidence, we employ a variety of techniques, including surveys, video talks, and focus groups around the world.

Contact Us:

Jagney Dave - Vice President of Client Engagement

Phone: +1-315 636 4242 (US) | +44- 20 3290 5010 (UK)

[johnndavid]

How to Speed Up UI Testing Without Compromising Quality

User Interface (UI) testing is a critical component of software development, ensuring that applications are not only functional but also user-friendly. However, as applications grow in complexity, UI testing can become a time-consuming and resource-intensive process. The challenge lies in accelerating UI testing without sacrificing the quality of the end product. In this article, we’ll explore practical strategies to achieve faster UI testing while maintaining high standards of quality. Additionally, we’ll highlight how leveraging advanced tools like vStellar can streamline the process.

Why UI Testing Matters

UI testing focuses on verifying the visual and functional aspects of an application’s user interface. It ensures that buttons, forms, menus, and other interactive elements work as intended and provide a seamless experience for users. Poor UI testing can lead to bugs, usability issues, and ultimately, dissatisfied customers. However, traditional UI testing methods often involve manual processes, which are slow, prone to human error, and difficult to scale.

To address these challenges, teams are increasingly adopting automated UI testing tools and optimizing their testing workflows. The goal is to reduce testing time while maintaining—or even improving—the quality of the application.

Challenges in UI Testing

Before diving into solutions, it’s important to understand the common challenges that slow down UI testing:

Manual Testing Bottlenecks: Manual testing is time-consuming and repetitive, especially for large applications with frequent updates.

Fragile Test Scripts: Automated test scripts can break easily when the UI changes, requiring constant maintenance.

Cross-Browser and Cross-Device Testing: Ensuring compatibility across multiple browsers and devices adds complexity and time to the testing process.

Resource Constraints: Limited access to testing environments, devices, or skilled testers can delay the process.

Flaky Tests: Unreliable tests that produce inconsistent results can waste time and reduce confidence in the testing process.

Strategies to Speed Up UI Testing

Here are proven strategies to accelerate UI testing without compromising quality:

1. Adopt Automated UI Testing Tools

Automation is key to speeding up UI testing. Automated testing tools can execute repetitive tasks faster and more accurately than manual testers. Tools like vStellar offer advanced features such as codeless test automation, cross-browser testing, and real-time reporting, making it easier to create and maintain test scripts.

By automating repetitive test cases, teams can focus their manual testing efforts on exploratory testing and edge cases, improving overall test coverage and efficiency.

2. Implement Parallel Testing

Running tests sequentially can be a major bottleneck. Parallel testing allows you to execute multiple test cases simultaneously across different browsers, devices, or environments. This significantly reduces the total testing time and helps identify compatibility issues faster.

For example, using a cloud-based testing platform, you can run tests on multiple devices and browsers in parallel, ensuring comprehensive coverage without extending the testing timeline.

3. Use AI-Powered Testing Tools

Artificial Intelligence (AI) is transforming UI testing by enabling smarter test creation, execution, and maintenance. AI-powered tools can automatically generate test cases, detect visual regressions, and even self-heal test scripts when the UI changes.

These tools reduce the manual effort required for test maintenance and help teams focus on higher-value tasks, such as improving test coverage and analyzing results.

4. Optimize Test Scripts

Fragile test scripts that break with every UI change can slow down the testing process. To avoid this, write robust and maintainable test scripts by:

Using reliable locators (e.g., CSS selectors or XPath) that are less likely to change.

Implementing modular test design to reuse code across multiple test cases.

Regularly reviewing and refactoring test scripts to eliminate redundancy.

5. Prioritize Test Cases

Not all test cases are equally important. Prioritize critical test cases that cover the most frequently used features and high-risk areas. This ensures that the most important aspects of the application are tested first, reducing the risk of major defects slipping through.

You can use risk-based testing or impact analysis to identify which test cases to prioritize.

6. Leverage Continuous Integration and Continuous Testing

Integrating UI testing into your Continuous Integration/Continuous Deployment (CI/CD) pipeline ensures that tests are run automatically with every code change. This helps catch issues early in the development cycle, reducing the time and cost of fixing them later.

Continuous testing also provides faster feedback to developers, enabling them to address issues promptly and keep the project on track.

7. Invest in Cross-Browser and Cross-Device Testing

Ensuring compatibility across different browsers and devices is essential for delivering a consistent user experience. However, manually testing on every combination can be impractical.

Use cloud-based testing platforms that provide access to a wide range of browsers and devices. These platforms allow you to run tests in parallel, reducing the time required for cross-browser and cross-device testing.

8. Monitor and Analyze Test Results

Effective test management involves monitoring test results and analyzing trends over time. Identify flaky tests, bottlenecks, and areas with high defect rates, and take corrective actions to improve the efficiency of your testing process.

Tools with built-in analytics and reporting features can help you gain insights into your testing process and make data-driven decisions.

How ui testing Can Help

One of the most effective ways to speed up UI testing is by leveraging advanced tools like vStellar. This platform offers a comprehensive suite of features designed to streamline the UI testing process, including:

Codeless Test Automation: Create automated test scripts without writing code, making it accessible to non-technical team members.

Cross-Browser Testing: Test your application on multiple browsers and devices simultaneously.

AI-Powered Capabilities: Automatically detect visual regressions and self-heal test scripts.

Real-Time Reporting: Get instant feedback on test results, enabling faster decision-making.

By integrating ui testing into your workflow, you can significantly reduce testing time while maintaining high standards of quality.

Best Practices for Faster UI Testing

To maximize the benefits of the strategies mentioned above, follow these best practices:

Start Early: Begin UI testing as early as possible in the development cycle to catch issues before they become costly to fix.

Collaborate Across Teams: Foster collaboration between developers, testers, and designers to ensure a shared understanding of requirements and expectations.

Regularly Update Test Cases: Keep your test cases up to date with the latest UI changes to avoid false positives and negatives.

Use Real Devices: Whenever possible, test on real devices rather than emulators to ensure accurate results.

Monitor Performance: Track the performance of your testing process and make adjustments as needed to improve efficiency.

Conclusion

Speeding up UI testing without compromising quality is achievable with the right strategies and tools. By adopting automation, implementing parallel testing, leveraging AI-powered tools, and optimizing your testing workflow, you can significantly reduce testing time while ensuring a high-quality user experience.

Platforms like vStellar play a crucial role in this process, offering advanced features that simplify and accelerate UI testing. By combining these tools with best practices and a focus on continuous improvement, you can deliver robust, user-friendly applications faster than ever before.

Investing in efficient UI testing not only saves time and resources but also enhances customer satisfaction, making it a win-win for both your team and your users.

[tonymattblog]

Codeless Test Automation: Revolutionizing Software Testing in 2025

Manual testing consumes time and resources. Automation speeds up the process, ensuring more accuracy. Traditional coding-based automation also has its challenges. These include long learning curves and maintenance issues.

Introducing Codeless Test Automation

Codeless test automation simplifies these struggles. It eliminates manual errors and reduces the skill requirement gap. With drag-and-drop features, quality assurance becomes quicker. Even non-technical people can create automated tests.

ideyaLabs Leads the Way

ideyaLabs excels in providing advanced codeless test automation solutions. Our products deliver accuracy, efficiency, and simplicity. Enterprises benefit greatly by reducing time-to-market. Save costs and improve software quality with our solutions.

How Codeless Test Automation Works

Codeless tools offer a user-friendly interface. These tools connect elements and interactions seamlessly. Visual workflow creation becomes straightforward. Our solutions support various platforms and applications. This versatility ensures comprehensive testing.

Benefits of Codeless Automation

Reduced Learning Time: No need for extensive coding knowledge. Teams can learn and implement faster.

Quick Set-up: Start automating tests much quicker.

High Accuracy: Minimize human error and enhance test precision.

Cost-effectiveness: Lower implementation and maintenance costs.

ideyaLabs' Exceptional Features

Ease of Use: Intuitive design for users across skill levels.

Scalability: Handle projects of any size. Adjust quickly to changing requirements.

Custom Reporting: Detailed insights into your tests. Make data-driven decisions.

Applications Across Industries

Codeless test automation benefits numerous industries. E-commerce, banking, healthcare, and more. The flexibility of tools allows them to cater to specific needs. Businesses can ensure seamless user experiences.

E-commerce Benefits

Faster Deployment: Automate tests for continuous integration. Updates and deployments become seamless.

User Experience: Ensure every feature works across devices and browsers.

Security: Identify and correct vulnerabilities faster.

Banking and Finance Advantages

Regulatory Compliance: Automate compliance testing easily.

Data Integrity: Ensure all transactions are correct and secure.

User Authentication: Verify multi-layer security features efficiently.

Healthcare Software Quality

Patient Data Security: Test systems for robust data protection.

Interoperability: Ensure various systems work in tandem.

Emergency Protocols: Validate critical system features without errors.

Emerging Trends in Codeless Test Automation

Artificial Intelligence: Integration of AI for smarter testing.

Machine Learning: Predictive analysis and adaptive testing models.

Cloud Testing: Execute tests on cloud-based platforms for extensive coverage.

ideyaLabs' Future Plans

Innovations: Continuously delivering the latest technology.

Customer Satisfaction: Focused on delivering top-notch client experiences.

Training Programs: Enhancing team skills for better adoption.

Why Choose ideyaLabs

Expert Team: Professionals with in-depth industry knowledge.

Proven Track Record: Successful implementations across diverse sectors.

Support and Maintenance: Reliable support structure for continual improvement.

Comparing Codeless Tools to Traditional Methods

Development Time: Traditional methods require more time to set up. Codeless tools expedite the process.

Skill Requirements: Traditional methods need specialized knowledge. Codeless tools are accessible to all team members.

Flexibility: Traditional tools might be rigid. Codeless tools adapt to changing needs easily.

Test Automation Best Practices

Start Simple: Automate repetitive, simple tasks first.

Regular Updates: Keep your test scenarios up-to-date with new features.

Monitor Results: Regularly check reports and fine-tune where necessary.

Collaboration: Encourage cross-team involvement in testing.

Case Studies and Success Stories

Many businesses have transformed with ideyaLabs’ solutions. From startups to large enterprises. They’ve seen a marked improvement in software quality and delivery times. Read about their journey on our blog and discover the difference.

Contact ideyaLabs for a Demo

Experience the power of codeless test automation first-hand. Contact ideyaLabs for a personalized demo. Let us show you how our solutions can revolutionize your testing processes.

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Conclusion

Codeless test automation is the future of software testing. Reduce errors, save time, and streamline your processes with ideyaLabs. Explore smarter, more efficient testing solutions for your business. Connect with ideyaLabs today. Transform your testing approach and experience unparalleled benefits.