Every year for the last four, Keysight has collaborated with faculty at the University of California Santa Cruz (UCSC) Baskin Engineering School to sponsor senior projects in test automation. This year, one of those projects focused on leveraging LLMs (Large Language Models) to improve the timeliness of responses to questions on the OpenTAP Forum.
Every year for the last four, Keysight has collaborated with faculty at the University of California Santa Cruz (UCSC) Baskin Engineering School to sponsor senior projects in test automation. This year (Spring 2024), one of those projects focused on leveraging LLMs (Large Language Models) to streamline the creation of OpenTAP plugins in Python.
Test automation, like the technology and products it targets, is in a state of constant change.
MarketsAndMarkets reports that the global test automation market size is expected to grow from USD 24.7 billion in 2022 to USD 52.7 billion by 2027, at a CAGR of 16.4%. To accompany the pace of the ever-changing testing landscape, you should be familiar with the latest test automation trends.
Artificial Intelligence (AI) is a focal domain for developers, for end-users and for the venture capital community. It’s as hot a commodity as Linux and open source were two decades ago. But AI and open source share more than just hype. Across natural language processing (NLP), Machine Learning (ML), Computer Vision, and Robotics, both AI and open source drive the democratization of technology, and open source is helping to drive the utility and ubiquity of AI platforms and applications.
