STARWEST 2019 - Big Data, Analytics, AI/Machine Learning for Testing
Monday, September 30
Test Data: Mining, Morphing, Managing and Maintaining It!
NewAccording to the 2018/2019 World Quality Report, the number one challenge in applying testing to agile development is overcoming the challenges of creating, managing, and maintaining test environments and test data. Over 48% of respondents had issues with test data. As our systems complexity and time to market demands have increased, the appetite for resolving the test data issue can be diminished or be viewed as test data doesn’t really matter. Join Julie Gardiner as she shares the good, bad and ugly of test environments and data, defines an approach to establish where you are in terms of...
Testing Today's Web Applications: Tools You Can Use
NewIf you are a software tester today, chances are you're testing a website or web application. Whether you are testing in a browser, within a web “wrapper” framework like Electron, or even in a web app wrapped in a mobile application, your customers are using web apps and websites constantly—and they want them to work well. Our challenge in testing, of course, is to test as thoroughly and efficiently as we can, given our time and resource constraints. Chris Kenst will demonstrate some of his favorite free and inexpensive tools for testing web apps and share stories of using these tools in...
Artificial Intelligence and Machine Learning Skills for the Testing World
PreviewSoftware continues to revolutionize the world, impacting nearly every aspect of our work, family, and personal life. Artificial intelligence (AI) and machine learning (ML) are playing key roles in this revolution through improvements in search results, recommendations, forecasts, and other predictions. AI and ML technologies are being used in platforms for digital assistants, home entertainment, medical diagnosis, customer support, and autonomous vehicles. Testing practitioners are recognizing the potential for advances in AI and ML to be leveraged for automated testing—an area...
Data Analytics and Machine Learning
Do you have access to lots and lots of test, development, app, and service data—really big data—from client and cloud service log files, test execution results, and more? Then, you have a great opportunity to begin using data analytics and machine learning (ML) to gain new product quality insights. Bring your laptops and your sense of discovery as Eun Chang introduce analysis techniques and ML tools to help you develop new and potentially groundbreaking insights. First, she will present a fast-paced statistics primer for those with no prior data exploration experience and others looking...
Tuesday, October 1
Testing Strategies for Microservices
Software development is trending toward building systems using small, autonomous, independently deployable services called microservices. Leveraging microservices makes it easier to add and modify system behavior with minimal or no service interruption. Because they facilitate releasing software early, frequently, and continuously, microservices are especially popular in DevOps. But how do microservices affect software testing and testability? Are there new testing challenges that arise from this paradigm? Or are these simply old challenges disguised as new ones? Join Tariq King as he...
Wednesday, October 2
From Zero to AI Hero
AI is here. Will it take over your job? Is it possible to make it beneficial, not detrimental to your career? Kevin Pyles and his team jumped right into the AI universe. Untrained and inexperienced, they realized immediately that they knew nothing, but they were motivated to learn and experiment so they could be part of this revolution. Kevin will show you how his team went from little knowledge of machine learning algorithms, artificial intelligence, and, in some cases, even programming and automation to implementing custom automation frameworks, data analytics, and machine learning....
What’s Our Job When the Machines Do Testing?
Members of the engineering community are beginning to explore the exciting capabilities of artificial intelligence in order to remove even more mundane and manual tasks from our jobs. The next generation of automation within the software development lifecycle comes to us in the form of AI-inspired approaches: analytics, machine learning, and natural language processing. Geoff Meyer refers to this as cognitive automation, and it offers the promise of automating tasks that up until now could only be performed by humans. However, engineering practitioners going down the path of cognitive...
Testing AI-Based Systems: A Gray-Box Approach
Testing artificial intelligence- and machine learning-based systems presents two key challenges. First, the same input can trigger different responses as the system learns and adapts to new conditions. Second, it tends to be difficult to determine exactly what the correct response of the system should be. Such system characteristics make test scenarios difficult to set up and reproduce and can cause us to lose confidence in test results. Yury Makedonov will explain how to test AI/ML-based systems by combining black box and white box testing techniques. His "gray box" testing approach...
Thursday, October 3
Testers: The Unsung Data Heroes
Connor Dodge believes that data is the most valuable commodity in the world, and that testers generate some of the most valuable data in product development organizations. Test data can inform release schedules, aid in decision-making, and shape the direction of the product. However, such benefits can only be realized if test data is effectively tracked and presented, and if testers learn how to present that data in compelling and persuasive ways. Join Connor as he talks about how testers can create and use real-time dashboards to analyze the status of agile projects and demonstrate the...
Smart Testing with AI Using Data Mining
The approaches to testing are continuously evolving as we try to keep up with the application needs of today’s users. Our industry is facing a new paradigm where AI is helping achieve scale, coverage, and business impact for many organizations that have been primarily focused on finding defects and refactoring test cases. Are your teams struggling to figure out how to leverage AI to improve their testing? To successfully do this, you must first understand one of AI’s underpinning foundations: data mining. Lorna Smyth will explain the fundamentals of data mining and how it is the base for...
Test Data as a Service: Fueling Quality at Speed
Any business that uses technology to interface with or provide service to their customers, suppliers, and partners requires customer-facing applications that have exceptional quality. The assurance of business outcomes must become an imperative for IT professionals, which means we must learn how to continually engineer quality into every product and process to provide confidence that our technology solutions protect the company brand. However, delivery within the required time frames is continually constrained by the quality, relevance, quantity, and security of test data. Join Michael...