Redefining Pre & Post Software Release Quality Practices with AI driven Automation
As software complexity grows, traditional QA methods struggle to keep pace. AI-driven automation enhances both pre- and post-release quality by integrating predictive analytics, intelligent test generation, and automated root cause analysis. Pre-release (Before deployment), AI improves defect prevention through automated testing and risk modeling, while post-release (After deployment), it enables proactive issue detection and continuous monitoring. Real-world AI implementations show efficiency gains in faster testing and defect resolution. By reducing defects and accelerating release cycles, AI transforms QA into a key enabler of DevOps agility and continuous integration & continuous deployment (CI/CD) efficiency.
Paper | Presentation
Felix Eu
Felix Eu is a former Software Quality Engineer at Intel Corporation based in Penang, Malaysia. He has over 20 years of experience in software engineering. He has held the Lean Six Sigma Green Badge since 2019, is a certified Software Quality Engineer (CSQE) from ASQ, and holds a Degree in Computer Science from the University of Bolton in the UK.
Mei Chen Ooi
Ooi Mei Chen has been in software engineering for over 12 years and has held many roles spanning code development, design, and project management. She is a senior System Software Quality Engineer at Intel Corporation based in Penang, Malaysia. She holds a Degree in Computer Science from the University Tunku Abdul Rahman, MY.
Wei Wooi Peh
Peh Wei Wooi is the Platform Validation Manager in the Intel Platform Integration & Validation (PID) organization. Before this role, he was a Software ADP Lead at Motorola Solutions. He has also been certified as an ISTQB (International Software Testing Qualifications Board) tester.
Yee Ven Koay
Koay Yee Ven is a System Software Quality Engineer with 21 years of extensive experience in software testing and quality assurance. She has held a Six Sigma Green Belt since 2016 and specializes in defect analysis, root cause analysis, software qualification, and process enhancement.