Transcription of Artificial intelligence-led quality assurance
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Artificial intelligence-led quality assurance
Applying machine intelligence to assurance practicesOur approach on Artificial intelligence (AI)/ machine learning (ML) based quality assurance is design based complying with the following steps - Discover > Learn > Sense>Respond cycle. The knowledge base constantly helps in storing and building pattern, which in turn helps in self-learning and responding to Suite Optimizer (TSO) Need: Growing test repository Duplicity or considerable overlap Huge regression suite versus short time boxed execution window Reduce automation effortBenefits: Test case optimization Upto 15 percent effort savings due to identification of similar test cases Structured Risk Based Testing Reduced Automation effortDiscover - Create smart assets using data repositories including defects, tickets, logs, etc.
Artificial Intelligence-led quality assurance Applying machine intelligence to assurance practices Our approach on artificial intelligence (AI)/ machine learning (ML) based quality assurance is design based complying with the following steps - Discover > Learn > Sense>Respond cycle. The knowledge base constantly helps in storing and building ...
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