QA Financial Milan

QA Financial Milan is Italy’s number one conference for software quality assurance experts. By attending this Chatham House Rule event, delegates gain key knowledge about the latest technologies and trends in the field, as well as test automation with a focus on the practical application of artificial intelligence (AI) to testing and quality assurance. The forum also discusses best practices to guarantee a solid DevOps infrastructure in order to ensure continuous integration and delivery (CI/CD). The forum is designed to promote the sharing of information between quality assurance and software architecture managers of financial companies with IT risk administrators and stakeholders, while ensuring confidentiality of the speakers.

As part of the program, Exactpro’s Anna-Maria Lukina gave a talk on Testing AI Systems: Quality Characteristics and Cognitive Biases:

“What are the quality characteristics which are specific to AI systems compared to traditional ones? What approaches can help to understand whether AI is robust enough?”

The presentation discussed the quality requirements for AI systems as well as the cognitive patterns affecting the process of validation and verification around them.

The full list of topics under discussion included:

  • Key technologies for test automation and CI/CD
  • Cloud testing virtualization
  • The new era of PSD2: the impact on API testing and Payment Platforms
  • Data-driven software: data management as the foundation for software development
  • You & AI: a journey towards the user experience of chatbots and virtual personal assistants
  • Performance and load testing, crowd testing and network testing
  • Testing Blockchain, Smart Contracts and Distributed Ledgers
  • Insurtech
  • Reality and fiction: the promise of AI and ML for the automation of QA
  • QA & QE: shifting left, DevOps and Agile methodologies
  • App security & DevSecOps: code quality and security

The official language of the event is Italian.

Related materials

Testing AI Systems: Quality Characteristics and Cognitive Biases