STAREAST 2025 - Big Data, Analytics, AI/Machine Learning for Testing
Sunday, April 27
Fundamentals of AI—ICAgile Certification (ICP-FAI)
Monday, April 28
Getting Started with AI-Driven Automation
AI has been rapidly changing the way we approach software testing. Traditional test automation is time-consuming to create and breaks down easily in the presence of change. Thankfully, AI is helping testing teams create less procedural, more resilient tests that are able to self-heal in the presence of modern, rapidly changing, highly dynamic production systems. This sounds great, but you may be asking yourself: How do I get started? What additional skills do I need to learn? What tools are available for me to start using, right now? Join Dionny Santiago as he breaks down different AI...
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, April 29
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,...
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, April 30
AI/ML SDET: A Title Change or a New Role?
Artificial Intelligence/Machine Learning Software Development Engineer in Test. What a title! But what does that person even do? Are they using AI/ML to test software? Are they testing AI or ML? This isn’t just a title change for a software tester, this is really a mind shift and tool change. What if you don’t even have a UI in which to test your product? What if you don’t ship a UI or even a product? The world of software is changing with advancements in AI/ML and it is time to make sure we level up our testing abilities to match the revolution. Join Kevin as he walks you through his...
Revolutionizing API Quality Assurance with Contract Testing and Error Code Analysis
In today’s microservices-driven landscape, ensuring seamless communication between services is critical. Traditional testing methods often fall short when it comes to detecting integration issues early in the development cycle, leading to unexpected failures in production. Contract testing is emerging as a powerful solution to this challenge, providing a way to verify that services meet agreed-upon expectations without relying on full end-to-end testing. This session will delve into the fundamentals of contract testing and how it enhances API quality assurance by detecting inconsistencies...
Is Your Playbook for Generative AI in Test Automation on Point?
Generative AI allows us to create test automation scripts really fast, but how can we be sure the outcome is truly complete? In this talk, Julio will discuss the critical process of how to define your prompts and evaluate if the results from AI-driven test automation creation cover all the necessary bases. He will bring a playbook for GenAI in test automation created based on the results of research that collected advice and feedback from dozens of test automation engineers. In the session, Julio will discuss practical examples of the mindset, a set of steps to be followed when using...
From Vision to Velocity: Accelerating Agile Testing with Generative AI
In the rapidly evolving landscape of Agile and DevOps, traditional methods of testing business-facing features often struggle to keep pace with the demands for faster and more thorough testing. However, the fusion of traditional testing wisdom with cutting-edge AI presents a unique opportunity to enhance software quality and delivery speed, offering innovative solutions to longstanding challenges. Join Phillip as he examines key test design techniques - such as equivalence partitioning, boundary value analysis, decision table testing, and state transition testing - and explores how...
Panel - Revolutionizing Test Automation: The Impact of Generative AI on Quality Engineering
As Generative AI rapidly reshapes how we work, its impact on quality engineering and more specifically test automation is profound. Join our panel of AI and testing experts as they dive into how Gen AI is transforming testing practices, from creating smarter automation frameworks to redefining manual testing roles. Explore cutting-edge tools, discuss the challenges of integrating AI into test strategies, and debate the ethical implications of AI-driven quality engineering. This thought-provoking session will be driven by your questions and thus provide actionable insights, inspire...
Thursday, May 1
Harnessing the Power of Large Language Models: Automatically Generating High-Quality, Readable, and Maintainable Unit Test Cases for Java and Python
In this talk, Lisa Waugh will discuss the challenges in delivering high-quality software due to manual testing and the need for automated unit test generation. Despite the development of techniques and tools to automatically generate unit tests, the generated tests often suffer from poor readability and lack resemblance to developer-written tests. To address these issues, Lisa's team has investigated the use of large language models (LLMs) to improve the readability and usability of automatically generated tests. They have created a pipeline to guide LLMs in generating high-coverage,...
Navigating the Future: Embracing Automation Testing in a Rapidly Evolving Digital World
In today’s rapidly evolving digital landscape, quality assurance is undergoing a major transformation. QA professionals must maintain software quality while adapting to the rapid pace of development, accelerated by AI. To keep up, the shift from manual testing to automation and AI-driven solutions is essential. This transition is not just about speed—it’s about fostering innovation, adaptability, and future readiness. However, adopting automation is complex, requiring team-wide processes and long-term maintenance for success. Where do you start? In this session, Amanda will share a five-...
Agentic Automation for Hyper Automation
In web and mobile automation, each phase is time-consuming and requires significant manual intervention. For example, purchasing a book from Amazon involves scripting the entire process: opening the browser, entering application details, providing payment information, and completing the purchase. Rajkumar J. Bhojan has a proposal on Hyper Automation which involves using Agents and Generative AI (GenAI) to streamline these tasks. Specifically, agents will create the necessary scripts to automate each phase, with each agent communicating with others to optimize results. To achieve this, Dr....
Automating the Testing of AI/ML Models: Tools, Skills, and Best Practices
As AI and ML models become integral to software systems, ensuring their accuracy and reliability through effective testing is paramount. Traditional testing approaches often fall short in addressing the unique challenges posed by these models, such as handling large datasets, verifying model predictions, and maintaining robustness against data drift. This presentation explores Otis Elevator's journey in automating the testing of AI/ML models using cutting-edge tools and techniques. Ayisha Tabbassum's team faced significant hurdles in manually testing their AI models, from the sheer volume...
Continuous Automation, It CAN Be Done!
Less than two years ago, Anupama's team faced a legacy portfolio with under 12% automation, minimal test coverage focused only on-screen verifications, data validation limited to spot checking few records resulting in low release confidence. Join her as she shares the organization's transformative journey towards robust test coverage and reliable releases through continuous automation. This strategy addresses process, people, and technology including: evaluating applications from user perspective to identify key automation opportunities, mapping production data flows allowed them to create...
Testing Under Pressure: Leveraging AI to Satisfy the C-Suite
In an era where "doing more with less" has become a corporate mantra, executives are increasingly turning to Artificial Intelligence (AI) to boost efficiency and productivity. This shift places significant pressure on testing teams to rapidly adopt AI solutions without compromising quality. In this engaging presentation, a C-suite executive and a testing expert offer a unique "fly on the wall" perspective into the dynamic between leadership expectations and the realities faced by testers. The session will delve into the challenges testers encounter under executive mandates, explore...
Friday, May 2
Balancing AI Innovations with Fundamental QA Principles
The pressure to adopt new technologies like AI and automation without a strong foundation in core QA principles is fraught with risk. Jumping into AI without understanding how to best leverage AI within QA for business success can cause quality issues. But lagging behind your competitors when it comes to utilizing AI can result in loss of market share. Join Igor Dorovskikh as he guides QA leaders on creating a balanced approach that integrates the use of AI capabilities within essential QA fundamentals. You'll learn how to define and implement these core principles, identify the pitfalls...