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Testing Tomorrow: Unravelling the AI in QA Beyond Automation
Testing Tomorrow: Unravelling the AI in QA Beyond Automation
Playlist
- Client Feedback & Quality Assurance in Web Design for Agencies
- Democratise Automation to Build Autonomy and Go-To-Market Faster
- Testing AWS applications locally and on CI with LocalStack
- Man Vs Machine: Finding (replicable) bugs post-release
- Shift-Left: Accelerating Quality Assurance in Agile Environments
- End-to-End Test Automation with Provar
- Fast-Tracking Project Delivery:Tips from a Recovering Perfectionist
- Crawl, Walk, Run...Fly - Take your build and test pipeline to the next level
- Revolutionizing Testing with Test Automation as a Service (TaaS)
- How Codemagic Mitigates Challenging Mobile App Testing Environments
- Fast and Furious: The Psychology of Web Performance
- Faster Feedback with Intelligent CD Pipelines
- Navigating the Future of Quality Engineering in 2024
- Using AI for Effective Test Generation
- Automated Test Execution Reporting
- How To Speed Up Our Work During Web Automation
- Building Products that Drive Better Results with Shortcut
- Shifting Accessibility Testing Left with LambdaTest and Evinced
- Testing Tomorrow: Unravelling the AI in QA Beyond Automation
- Flaky Tests from an Engineering Perspective
- Future Trends and Innovations in Gen AI for Quality Engineering
- Mastering User-Centric Mindset Unlocking Your Potential as a Tester
- From Brainwave to Inbox: Avo's Whimsical Adventure through AI-Powered Test Automation
- The Myth of โBest Practiceโ
- Impact and Potentials of GenAI to the IT Engineers
- Innovation Accelerated: The Intersection of AI and Quality Engineering
- Optimize Issue Tracking: Integrating SpiraTeam with LambdaTest
- The Power of Generative AI in Reducing Maintenance and Enhancing Speed
- Rethinking the Role of QA Profile
- Building Quality Software: AI-based testing approach with Jira and QMetry
- In-Depth with Playwright: A Modern Testing Framework
- Supercharge Your Data Quality Testing with AI/ML
- GenAI for Quality Transformation
- Creating Reliable and Scalable Test Automation Frameworks
- Upskilling Quality Engineers: A Success Story in SDET Transformation
- AI-Readiness: Are You Building the Future or Falling Behind
- Leading the Charge in Software Quality with Zero Bug Revolution
- Building a Test Automation Framework for TV Apps & Scaling at FX Digital
- Building High-Quality Teams: People, Process & Proof for QA Leadership
- Why Do We Have Bugs, and Why Do They Happen?
- GenAI in QA: Tiket's Approach to Evolving Quality Engineering
- Collaborative Remote Testing: How to Set Up & Run Effective Ensemble Sessions
- Simulating Real-World Scenarios: Balancing Precision and Practicality in Testing
- Building AI-Driven Test Automation Frameworks for QA Excellence : Challenges with Agile, DevOps, and AI-driven Testing
- Reinforcing Cybersecurity Beyond Functional Testing
- Building AI-Driven Test Automation Frameworks for QA Excellence
- Shift Happens: Driving Quality LeftโA Real-World Journey Across Five Teams
- Transitioning from Manual Testing to Test Automation with Cypress
- See Why Your Testing Framework Is Incorrect, Incomplete, or Inefficient โ And Iโll Show You Why
- Quality First: Implementing Shift-Left Testing for Future-Ready Products
- Building Resilient Quality Engineering Teams: Exploring Emerging Trends and Best Practices
- Testing LLMs: Why It Matters, Common Data Challenges, and Proven Testing Strategies
- Observability in Software Test Modernization
- AARRR...Are you Test-Ready for AI? Discover If AI Can Transform QA Process
- Integrating Testing into Agile Workflows: Enabling Faster, Smarter Software Delivery
About The Video
Watch the latest episode of the XP Series webinar with our speaker ๐๐ซ๐๐๐๐๐ฉ ๐๐จ๐ฎ๐ง๐๐๐ซ๐๐ซ๐๐ฃ๐๐ง, Founder & CEO, Moolya & Bugasura. Tune in for an insightful discussion on "Testing Tomorrow: Unravelling the AI in QA Beyond Automation".
In this episode, Pradeep dives into the ever-evolving landscape of software testing, emphasizing AI-driven strategies discussing how artificial intelligence is revolutionizing traditional testing methodologies, and shedding light on the challenges and opportunities it presents. Through real-world examples, he illustrates successful AI implementations in testing and explores futuristic trends that testers should watch. Don't miss the insights on developments in the context-driven testing arena.
Key Topics Covered
Introduction to AI in Testing: Pradeep starts by emphasizing how AI has been integrated into various aspects of technology and how it's being used to solve existing problems in the software testing domain. He stresses that while AI presents new solutions, it also highlights issues that existed even before its widespread adoption.
Challenges and Opportunities with AI in Testing: He discusses the dual nature of AI in testing - how it offers solutions to long-standing problems but also introduces new challenges, particularly in terms of data availability and the applicability of AI in creating meaningful test cases.
Context-Driven Testing vs. Traditional Testing: Pradeep contrasts traditional testing methods, which often rely heavily on requirements documents, with context-driven testing that considers a broader range of factors affecting testing strategies and outcomes.
The Importance of a Context-Driven Mindset: He highlights how adopting a context-driven approach in today's testing landscape allows for a more nuanced and effective testing strategy that aligns closely with real-world user experiences and product contexts.
Growth-Driven Testing: Pradeep introduces the concept of growth-driven testing, a methodology that focuses on aligning testing efforts with business growth, customer satisfaction, and the broader objectives of the organization.
Impact-Oriented Testing: The discussion also covers how impact-oriented testing ensures software quality by focusing testing efforts on areas that significantly affect the user experience and business outcomes.
Ethical Considerations in AI Testing: The conversation touches on ethical concerns related to AI in testing, especially around data privacy and bias. Pradeep emphasizes the responsibility of those developing AI systems to consider these ethical dimensions.
Future Projects and Innovations: Pradeep shares insights into new projects and innovations from Moolya & AppAchhi, aiming to address current challenges in the testing space through context-driven and AI-enhanced testing solutions.
Final Thoughts on AI and Quality Assurance: He concludes with advice for testers in the evolving landscape of software testing, highlighting the importance of adaptability and the need for testers to remain flexible and open to new technologies and methodologies.
Related Blogs & Hubs
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LambdaTest
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