InfoQ Homepage Automation Content on InfoQ
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Reaching Your Automatic Testing Goals by Enhancing Your Test Architecture
If you have automatic end-to-end tests, you have test architecture, even if you’ve never given it a thought. Test architecture encompasses everything from code to more theoretical concerns like enterprise architecture, but with concrete, immediate consequences. Let's explore how you can achieve the goals you have for your automatic testing effort.
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Cell-Based Architecture Adoption Guidelines
The challenges in building modern, reliable, and understandable distributed systems continue to grow, and cell-based architecture is a valuable way to accept, isolate, and stay reliable in the face of failures. Organizations must ensure that the cell-based architecture is the right fit for them and that the migration will not cause more problems than it solves.
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Mastering Impact Analysis and Optimizing Change Release Processes
Dynamic IT professional with a proven track record in optimizing production processes and analyzing outages in complex systems handling millions of TPS. The recent CrowdStrike outage highlights the importance of continuous improvement and adherence to best practices. Passionate about elevating operational excellence through strategic reviews and effective process enhancements.
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How Quality Champions Foster Sustainable Software Quality Improvement at Swiss Post
Even skilled and motivated agile teams sometimes fail to achieve their own software quality goals. In this article, we present a practice we use to assist agile teams in reaching their quality goals and share our experience. The practice is about paying constant attention to specific metrics. It means encouraging people to improve themselves in both qualitative and quantitative ways.
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Delivering Great Developer Experiences with Platform Engineering
Companies increasingly turn to platform engineering to help scale their development teams and increase developer experience for engineer efficiency. In this virtual panel, we’ll discuss how teams build platforms, set others up for success, work with developers who use their platform, measure their progress, and adapt to new challenges.
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Testing Machine Learning: Insight and Experience from Using Simulators to Test Trained Functionality
When testing machine learning systems, we must apply existing test processes and methods differently. Machine Learning applications consist of a few lines of code, with complex networks of weighted data points that form the implementation. The data used in training is where the functionality is ultimately defined, and that is where you will find your issues and bugs.
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Creating Your Own AI Co-Author Using C++
While using ChatGPT through a web interface is one thing, creating your own autonomous AI tool that interfaces with ChatGPT via its API is a different story altogether. As strong proponents of C++, in this article we are going to present a GPT tool written in C++ to ease the pain of dealing with the daunting task of editing endless editorial comments.
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Thinking Deductively to Understand Complex Software Systems
Thinking differently can allow us to approach problems in new ways. With testing, approaching the problem with a negative approach can lead to more thorough test cases.
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If You Want to Deliver Fast, Your Tests Have the Last Word
A good testing strategy is critical for safe code changes, fast delivery, reduced MTTR, and improved developer experience. Shifting the concept of “unit” can reduce the time needed for changes.
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Effective Test Automation Approaches for Modern CI/CD Pipelines
Shifting left can be used to improve test design and lead to faster, more effective CI/CD pipelines. By focusing on building effective and efficient tests, CI/CD runs can quickly return feedback.
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A Simpler Testing Pyramid: Getting the Most out of Your Tests
Overcomplicating your test structure can lead to slow, brittle tests. A focus on test speed as the primary labeling mechanism maximizes your test investment.
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Moving towards a Future of Testing in the Metaverse
In this article, Tariq King describes the metaverse concept, discusses its key engineering challenges and quality concerns, and then walks through recent technological advances in AI and software testing that are helping to mitigate these challenges. To wrap up, he shares some of his thoughts on the role of software testers as we move towards a future of testing in the metaverse.