E-BOOK

Software Quality at the Forefront: AI-Powered Testing Strategies for Enterprises in 2024

In an era where every business move is a sprint, ensuring the highest quality software is more crucial than ever. Software Quality at the Forefront offers a deep dive into the innovative realm of AI-powered testing, a method that has transformed how enterprises operate in 2024.

From cutting down extensive testing cycles to preventing untested code changes from affecting production, this eBook encapsulates the essence of modern testing strategies. Readers will uncover the true power of Test Impact Analytics, a groundbreaking approach that intelligently streamlines testing cycles. With the unique focus on the “Shift Left” philosophy, the book details the importance of identifying risks earlier in the development process. Additionally, it highlights the often-overlooked connection between user stories and untested code changes, presenting comprehensive solutions to bridge the gap.

Incorporating insights from SeaLights, this guide is perfect for Development and QA teams striving to stay ahead of the curve. Discover the AI advantage, understand the importance of shifting left, and learn strategies to ensure that every line of code aligns with the desired user story.
Key Takeaways:

  • Streamline Test Cycles: Unveil the potential of Test Impact Analytics to cut short testing durations and increase efficiency.
  • Maintain Quality: Set quality policies that prevent untested code changes from moving to production, ensuring only the highest quality code makes the cut.
  • Early Risk Identification: Understand the importance of “Shift Left” and how Test Impact Analytics on Pull Request can save resources and reduce bug-related costs.
  • Bridge the Disconnect: Dive deep into the chasm between user stories and untested code changes and explore game-changing solutions.
Who This eBook Is For: Development and QA professionals, software engineers, enterprise decision-makers, and anyone keen on leveraging AI to revolutionize their software testing processes.

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