Agile + DevOps East 2023 - AI/ML - Track 2
Wednesday, November 8
Exploring Non-ChatGPT Ways to Use AI in Testing
Artificial intelligence and machine learning tools like ChatGPT are bringing AI to the public. The goal and purpose of code generation and refactoring tools like GitHub’s Co-Pilot are evident. However, it may not be as obvious to tell which tools are specifically tailored for testing and quality engineering. Join Carlos Kidman as he compares multiple AI/ML tools and practical applications that testers and quality engineers can use right now. You’ll discover AI for functional testing solutions and tools for test data management. While not all of these tools are free, this session will give...
AI in DevOps for Improving Engineering Team Productivity
AI and machine learning continue to be hot topics everywhere. The majority of discussions on AI/ML are focused on how generative AI and large language models (LLMs) will change the world. However, LLMs like ChatGPT, Bard, and Llama only represent one area of modern advances in the AI/ML space. Considering the bigger picture of new AI technologies, Chris Navrides has been investigating ways to enable entire new areas of opportunity within the DevOps lifecycle. By leveraging AI in DevOps, he believes teams can improve developer productivity through better code authoring, debugging, and...
From Bottlenecks to Breakthroughs: Using AI in Performance
Performance, a cornerstone of delivering high-quality software, is poised to undergo a seismic shift, and artificial intelligence (AI) is at the helm. Yet, as with many technological evolutions, there's a haze of misconception surrounding AI's role in this domain. Is AI merely an advanced tool, or can it redefine the entire engineering paradigm? Join Kaushal Dalvi as he demystifies AI's transformative role in performance. Drawing from real-world experiences and case studies, covering AI's potential in auto-generation of performance tests and predicting bottlenecks. Engage in interactive...
Thursday, November 9
Transforming User Requirements to Test Cases Using Model-Driven Software Engineering and Natural Language Processing
Testing continues to be the main approach to ensuring software quality during development. Although there have been many attempts to automate the generation of test cases from user requirements (formal or informal), creating test cases continues to be mainly a manual process. However, many studies have shown that automating the generation of test cases from requirements can substantially reduce costs and improve the efficiency of the testing process. Test automation has also been proven to show positive effects on software quality. With the advances in Model-driven Software Engineering (...
Transforming Testing with Generative AI: A Demonstration
Are you looking to improve the efficiency and effectiveness of the agile testing process? Join and explore the future of agile testing with Generative AI. In agile software development, feature grooming, refinement, user story generation, acceptance testing, and test automation are all critical steps to ensure system quality. While these steps are critical to the project's success, they are not always handled effectively. They can be time-consuming and things like writing test cases and automation code can be labor-intensive and often fall short of covering all requirements. To address...