STARWEST 2021 - Big Data, Analytics, AI/Machine Learning for Testing

Software 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 that still...

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...

The use of AI for testing is one of the latest trends in the software industry. Within the last decade, there has been a vast increase in the number of vendors and startup companies promoting AI-driven test automation tools, platforms or frameworks. But what are the real benefits of this technology? Does it have any weaknesses? Are all AI technologies created equally? Join Tariq King as takes you on a journey and shows you the true strength of AI in testing. In this tour de force, Tariq will describe some of the recent advances in AI-driven test automation, while keeping it down to earth...

Testing is a crucial enabler for the success of chatbots and voice assistants. Doing it manually requires enormous time and effort. As DevOps and furthermore AIOps grow in importance, automated testing will remain critical to ensure that bots actually do what their designers intend. Unlike traditional software where the application follows a predefined flow, a chatbot runs without any restrictions. Talking to a chatbot has no barriers. Combining this with an unpredictable user behavior, it becomes utmost difficult to verify the correctness of conversational AI. Training data and test sets...