Journey towards Zero Defects: Challenges, Best Practices and Testing Models
By: Wipro View more from Wipro >>
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4 stages of your end-to-end voice testing lifecycle
By: Hammer
Type: eBook
For many organizations who are struggling with their voice and contact center technologies, end-to-end testing may be the right solution for their needs.
However, due to a handful of challenges during its lifecycle stages, and with so many testing strategies available, some can be daunted by the process and can be unsure of where to start.
This guide can provide you with insight into the modern voice landscape, offering a look at the 4 lifecycle stages you should know in order to meet customer expectations.
Browse the guide to learn more.
These are also closely related to: "Journey towards Zero Defects: Challenges, Best Practices and Testing Models"
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DevOps Maturity: Crafting a baseline & continuous growth plan
By: Qualitest Group
Type: White Paper
This white paper discusses how large enterprises can drive DevOps maturity with a maturity roadmap. It outlines five stages of DevOps transformation, from Aspirational to NextGen, that build on each other.
Your dev teams can use maturity models to establish a baseline, identify gaps, and create a quarterly plan to reach higher levels. Key recommendations include empowering teams to own their maturity journey, getting stakeholder buy-in, and fostering continuous learning.
To learn more strategies for transforming your DevOps practices, read the full white paper.
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Using Machine Learning to predict vulnerabilities in software testing
By: Qualitest Group
Type: White Paper
This white paper examines how machine learning (ML) can improve testing methods. It also discusses the differences in the modern approach to testing which involves both automation and manual testing, and how testing can be improved using machine learning algorithms.
Highlights from the paper include:
- ML's role in automating test case creation, script upkeep, and defect forecasting to boost efficiency
- Using Bayes' Theorem for pinpointing high-risk areas in testing
- ML in testing shortening regression periods from weeks to days
Discover more in the full report.
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