The
Future Of Test Automation

In this episode of “The Future Of,” Jeff Dance speaks with Elijah Kerry, Software Director at National Instruments, to explore the evolving landscape of test automation. Elijah shares insights from nearly two decades in the test and measurement industry, including the growing importance of software skills among engineers, the critical role of testing for reliable hardware and software at scale, and the dynamic interplay between tools like LabVIEW and Python. They discuss the increasing impact of AI, containerization, and distributed systems, emphasizing the ethical responsibilities and cybersecurity considerations for the future. The conversation highlights the continuing evolution of test automation and its importance in ensuring technological innovation is both safe and reliable.

Evolution in Test Automation

• Transition to Complexity: The industry has shifted from simple laboratory automation to highly complex systems, requiring engineers (mechanical, electrical, etc.) to master sophisticated software concepts.

• Standardization of Best Practices: Over the last two decades, best practices like source code control have replaced manual methods like “final” and “final2” zip files.

• The “Cool Factor” of Test: While often underappreciated compared to design, test engineering is gaining recognition as an exciting field where engineers push products to failure to ensure innovation actually works.

LabVIEW vs. Python for Test Automation

• Right Tool for the Job: Python is highly regarded for rapid prototyping and its vast ecosystem, while LabVIEW remains the leader for mission-critical, high-performance systems.

• Interacting with the Physical World: LabVIEW’s graphical data flow syntax is uniquely designed to manage the concurrent and asynchronous nature of talking to multiple physical devices.

• Ecosystem Synergy: Rather than seeing them as competitors, the industry is increasingly using LabVIEW and Python as complementary tools within the same application.

The Role of AI and Future Technologies

• AI Assistants: NI is integrating AI assistants (using LLMs like ChatGPT) to help users understand inherited code, find IP, and eventually generate code.

• Enhanced Operations: AI is being leveraged beyond development to assist in hardware selection, system integration, and managing the thermal and interference challenges of physical signals.

• Predictive Data Analysis: AI and LLMs are used to intelligently predict product quality and longevity by correlating massive amounts of test data with real-world outcomes.

• Containerization: The adoption of Docker and containers allows test software to be more resilient, enabling independent component updates and distributed system architectures.

Ethics, Cybersecurity, and Collaboration

• Ethical Obligation: Test automation provides the ethical underpinning for critical safety systems, ensuring that devices like pacemakers and autopilot systems are reliable.

• Cybersecurity Focus: In response to aggressive global regulations, significant resources are being invested to strengthen the security and resilience of test tools against AI-powered attackers.

• Global Community: User groups and events like GDevCon serve as vital forums for community-led innovation, with NI increasingly open-sourcing libraries to empower user contributions.

• Renewed Investment: Under Emerson’s ownership, there is a strengthened commitment to core technologies like LabVIEW and new portfolios of DAQ (Data Acquisition) products.