Artificial Intelligence & Software Testing: Hype or Hysteria?

Artificial Intelligence & Software Testing: Hype or Hysteria?

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  Artificial Intelligence & SoftwareTesting: Hype or Hysteria? Johan Steyn
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  Picture credit: FranckV. on Unsplash What is your view of Artificial Intelligence
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  Hype Hysteria
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  2030
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  How will allthis impact Software Quality & Testing? How will all this impact YOU?
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  Source: https://www.tricentis.com/artificial-intelligence-software-testing/
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  Key recommendation: Investin intelligent self-learning QA and Testing platforms for all areas of the application landscape. "Intelligence-driven QA" - invest and experiment with tools that will analyse the root cause of defects, analyse coverage and efficiency of test sets; analyse utilisation of resources and environments; predict test estimation based on requirements; predict risk areas and risk levels in projects; plan the priority of test cases. Robotics will bring down the headcount in the QA and testing function as these machines take on the more repetitive analysis and execution tasks and routine jobs currently undertaken by humans.
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  The convergence ofphysical with the cyber has added another layer of complexity to the testing activity. Product strategy is shifting from building discrete products to building connected eco-systems. In the digital age, we need to test for experience rather than functions or features. As we enter the realm of early AI testing it is critical to building knowledge based on artefacts we already collect like defect log data, life cycle information, fields defects, and production events to improve effectiveness. The book concludes with an interesting perspective on the digital quality engineering skills that an AI quality engineer needs. This can be used as a ready reckoner when setting up cross-functional testing teams armed with the right digital test engineering skills.
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  By most estimates,AI will create a market worth over $35 billion by 2025 and double annual economic growth rates, promising a future of robots and humans working together to solve the world’s most difficult problems—side by side and armed with near-unlimited processing and algorithmic power. In South Africa... companies find themselves encumbered by legacy technologies and systems, business models, and corporate structures, as well as sunk investments in antiquated infrastructure—all with workforces that may not be ready for the AI revolution that is already underway cross the globe. • Create a vibrant ecosystem • Universities / education • Start-ups • Large firms invest in the technology • Policymakers/government
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  • The businesscase for AI in testing • AI in the larger organisation • AI and transformation/change management • Embarking on an AI journey • Testing vendors & offshore testing centres • Testing AI systems • Big Data and AI in testing • AI Cloud / AI-as-a-service
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  Source: https://youtu.be/Y9FOyoS3Fag