STARWEST 2024 - Big Data, Analytics, AI/Machine Learning for Testing
Sunday, September 22
DevOps for AI and Machine Learning
Fundamentals of AI—ICAgile Certification (ICP-FAI)
Software Test Management, Planning, and Measurement
Monday, September 23
Evaluating and Testing Generative AI: Insights and Strategies
Generative AI (GenAI), exemplified by groundbreaking systems like ChatGPT and LLAMA, is revolutionizing the software landscape. These advanced technologies represent some of the most sophisticated software ever devised, capable of navigating an unprecedented range of prompts and questions, many of which have never been posed in human history. Their ability to generate varied responses to the same query and even fabricate answers when uncertain poses unique challenges in verification and testing. This talk delves into the intricacies of validating such systems and identifies areas needing...
Full-Stack Testing for Microservices Architectures
Software development is trending toward building systems using small, autonomous, independently deployable microservices. Leveraging microservices makes it easier to release software early, more frequently, and even continuously, which aligns well with Agile and DevOps. But how does the microservices architectural pattern affect software testing and testability? How can you ensure microservice-based applications have an adequate level of test coverage at each level? Does this paradigm change the test automation pyramid, and if so what does that look like? Join Tariq King as he walks...
Tuesday, September 24
Supercharge Your Workflow: To GitHub and Beyond
Whether you are new or experienced with GitHub this class is for you! Supercharging your workflow caters to anyone who wants to enhance their Agile and DevOps process with the capabilities of GitHub. GitHub has long been the premier site for open-source projects and is now turning a pivotal corner into becoming the predominant platform for all aspects of the development lifecycle. Some examples of this include; protecting company code through various GitHub Products or curating marketplace actions and workflows prior to use. This tutorial will look at how to leverage GitHub Actions (CI/CD...
A Quality Engineering Introduction to AI and Machine Learning
Although there are several controversies and misunderstandings surrounding AI and machine learning, one thing is apparent — people have quality concerns about the safety, reliability, and trustworthiness of these types of systems. Not only are ML-based systems shrouded in mystery due to their largely black-box nature, they also tend to be unpredictable since they can adapt and learn new things at runtime. Validating ML systems is challenging and requires a cross-section of knowledge, skills, and experience from areas such as mathematics, data science, software engineering, cyber-security,...
Harnessing Generative AI in Software Testing: A Real-World Guide
The advent of Generative AI (GenAI), including Large Language Models (LLMs) and tools like ChatGPT, is not just another technological shift—it's a paradigm change, particularly in the realm of software testing. Unlike the transitions to mobile or cloud computing, GenAI introduces both unparalleled utility and disruption in software quality assurance. This session is dedicated to demystifying GenAI in software testing, distinguishing hype from reality, and providing practical tools and techniques to enhance your team's software quality while also highlighting potential pitfalls and...
Prompt Engineering for Software Quality Professionals
With the sudden rise of ChatGPT and large language models (LLMs), professionals have been attempting to use these types of tools to improve productivity. Building off prior momentum in AI for testing, software quality professionals are leveraging LLMs for creating tests, generating test scripts, automatically analyzing test results, and more. However, if LLM's are not fed good prompts describing the task that the AI is supposed to perform, their responses can be inaccurate and unreliable, thereby diminishing productivity gains. Join Tariq King as he teaches you how to craft high-quality AI...
AI-Assisted Testing: Using GitHub Copilot and Other Tools to Accelerate QA
There is no question that Generative AI models can improve the productivity of almost every role within the software development process. However, while a lot of attention has focused on generating software using tools such as GitHub Copilot, Amazon CodeWhisperer, Tabnine, and more, these tools can assist software testers in their job too. Join Coveros CEO Jeffery Payne to explore how Generative AI solutions help software testers generate and supplement tests, create automated test scripts, and even suggest improvements to what you’ve already created. Learn how AI can increase test...
Wednesday, September 25
Generative AI is Transforming Software Testing: What Testers Need to Know
We have all seen it. The word AI is appearing next to every test tool, and the promises are coming thick and fast. AI seems like the perfect addition to increase the quality of the tests we run, but what if the opposite is true, and it’s the death of quality engineering as we know it? There has been no greater transformation in test quality than test automation in the last decade. We have gone through the horrible years of record and replay automation that never provided the ROI that was promised, and we finally settled on automation engineering, where we treat our automation code with the...
Reinventing the Art of Software Testing with Google Cloud AI Platform
This session explores the innovative ways to approach and revolutionize the art software testing by harnessing the full power of Google Cloud AI Platform. Utilizing AI-powered regression testing and natural language processing (NLP) capabilities, developers can automate mundane and repetitive tests while also analyzing software functionality and usability. Predictive analytics and custom machine learning models can be used to anticipate and identify potential issues, improve testing efficiency, and provide actionable insights. Applying reinforcement learning algorithms for GUI testing,...
Kafka and Kafka Testing: Streamlining Real-time Data Processing
In today's data-driven landscape, real-time data processing is the backbone of modern applications. Kafka, a distributed event streaming platform, has emerged as a critical component in building data-intensive systems. This presentation provides an in-depth exploration of Kafka and the essential practice of Kafka testing, offering attendees valuable insights into harnessing the power of real-time data streams while ensuring robust system reliability. Key topics to be covered are: an introduction to Kafka to understand Kafka's architecture and core components, importance of Kafka Testing,...
AI in Testing: A Moderated Panel Discussion
Artificial intelligence is the newest trend in software testing. But what is it, and how will it impact the tester's role, both today and in the future? What do you need to do to embrace this emerging technology? Tariq King will moderate this panel discussion to give you an opportunity to hear the opinions of industry leaders about AI in testing. You will have a chance to drive the debate, so come prepared with all your AI questions.
Thursday, September 26
Revenge of the Nerds: How to Build a Tech Career Niche in the AI-verse
A major question so many of us have on our minds is, HOW do I shift my career to something related to AI so I can stay relevant? This has been coming from industry professionals as well as college grads/new job seekers across ALL industries. QA is no exception! Dona shifted her career to an AI niche in the past year and have hassled and helped many others do the same thing. She want to help YOU do it, too. Let's discuss. What is AI today? What are the five skill sets relevant in the AI-verse? How can you create a career niche in the AI-verse based on your industry and goals? Lastly, Dona...
Bridging AI-Generated Acceptance Criteria with Comprehensive Test Scenarios
The generation of acceptance criteria through generative AI is an innovative approach to streamline the requirements gathering process. However, ensuring that the implemented code aligns with these criteria is crucial for delivering high-quality software. This talk explores the integration of generative AI generating acceptance criteria with test case scenarios, aiming to establish a seamless connection between the development and testing phases. By leveraging pull requests as a central hub, this approach facilitates the validation of whether the test case scenarios adequately cover the...
Change: It's All We Have
As philosopher Heraclitus once said, “The only thing that is constant is change.” Which means that when stop fighting change, stop staying stuck in “the way things have always been” and START embracing the power of change—within our mindsets, offices, objectives—we START transforming into the most relevant and resonant versions of ourselves, our teams, and our organizations. As a change-agent both inside technology and WAY OUTSIDE, this interactive (and fun) session is focused on you gaining the clarity, creativity, and confidence necessary to wield the power of change and have impact...
Tips for Building LLM Apps
The barrier to entry for AI, specifically Large Language Models (LLM), is low and we can take advantage of them in our own tools, projects, and apps. In this session, we’ll build a simple app that uses an LLM which will help us cover: The steps to using AI in a program. LLM Basics. Pick the right LLM. Data Preparation. Evals and Testing. Insights and issues to consider. Tips that you can use as you build your own. Join us for a hands-on session that will help you build your first LLM app or level up your current project!
Multi-Modal GPTs Are Coming For Your Testing! How to Adapt?
As you research the latest in generative AI technology, you will see that the development and availability of multi-modal GPT engines are fundamentally changing the way applications are tested and described. These new GPT models can generate and interpret voice, text, and images seamlessly. For example, you can ask them to navigate an application to accomplish a business task and comment on their actions. This means that we’re for the first time entering the world of AI-assisted/performed exploratory testing. When you couple this with the capabilities of GPT models to identify UI elements...