Everywhere you turn, someone is bringing up AI. No wonder some people roll their eyes at the mention of artificial intelligence.
Artificial intelligence has rapidly transitioned from buzzword to foundational technology in software testing, according to Mike Wager, technology expert at Keysight Technologies.
“Everywhere you turn, AI seems to dominate conversations,” Wager shared. “For some, it’s merely smoke and mirrors, a glorified spreadsheet. But we’re past that misconception. AI is genuinely transforming software testing.”
Wager outlined a structured approach Keysight uses called the “Thinking, Creating, and Learning Framework,” which simplifies AI into three essential functions.
First, thinking. “Decision-making and adaptability, aligning with Agentic AI’s ability to make real-time data-driven choices,” he said.
Secondly, creating, namely “leveraging Generative AI to autonomously produce test cases and user scenarios.”
Finally, learning. “Rooted in traditional machine learning methods first described by Alan Turing, enabling continuous improvement from historical data,” he explained.
“For some, AI is merely smoke and mirrors, a glorified spreadsheet. But we’re past that misconception.”
– Mike Wager
But what’s the practical impact? Does it matter to the industry?
“Absolutely,” argued Wager. “These AI functions significantly impact testing efficiency, accuracy, and resource management.”
Tracing AI’s roots in software testing back to Alan Turing’s pioneering concepts from 1947, Wager singled out Keysight Eggplant’s advancements.
“In 2018, we integrated machine learning into our Digital Automation Intelligence (DAI) platform, now Eggplant Test. It revolutionized how testing is done,” he claimed.
Eggplant Test automates crucial processes such as identifying user journeys, prioritizing critical test cases, detecting anomalies early, and dynamically adapting scripts to software changes.
“Imagine changing a payment gateway and having new test cases auto-generated without manual intervention—that’s intelligent automation at work,” explained Wager.
Generative AI represents the next wave, aiming to automate test creation directly from software requirements documents. But security remains critical.
“Our Generative AI solutions will run offline, on-premises,” Wager noted. “Unlike cloud-based tools, we provide complete data control, eliminating security threats like ‘shadow prompting.”
“Cloud-based AI poses serious compliance risks.”
– Mike Wager
Agentic AI, the latest evolution, introduces intelligent agents capable of autonomous test design and execution. Using sophisticated techniques like chain-of-thought reasoning, these agents handle complex interactions and edge cases, crucial for rigorous end-to-end testing.
Additionally, Eggplant integrates advanced models such as computer use agents (CUAs) and large vision models (LLaVA), critical for automating intricate browser-based tasks and visual validations.
Wager underscored Keysight’s commitment to compliance and data security.
“Cloud-based AI poses serious compliance risks. Industries cannot compromise on data security. Our offline, on-premises AI solutions adhere strictly to GDPR, the EU AI Act, and other global regulations.”
Looking forward, Wager sees AI as essential for future-proofing software testing.
“It’s not about following the latest trends. It’s about strategic innovation that maintains security, scalability, and compliance,” he concluded.
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