More code. Faster releases. Less confidence. That's the AI coding paradox. Most engineering leaders know their QA capacity is lagging. Few have the data to prove it. AI accelerated your development velocity. Did your testing keep pace?
Why Your Software Engineering Metrics Need to Go Beyond DORA in 2026

Why Your Software Engineering Metrics Need to Go Beyond DORA in 2026

Publish Date: April 27, 2026

DORA scores look great, but production still breaks. In 2026, elite engineering leaders are closing the gap with software engineering metrics that track AI code quality, developer experience, and real business outcomes, not just deployment speed.

20 Must-Have QA Metrics for Better Test Management

20 Must-Have QA Metrics for Better Test Management

Publish Date: July 7, 2025

Gain deeper insights into software quality with 20 essential QA metrics. Improve test management efficiency and decision-making by leveraging metrics that cover test coverage, defect trends, execution rates, and overall testing performance.

How Improper QA Reporting Can Hinder Software Quality Success

How Improper QA Reporting Can Hinder Software Quality Success

Publish Date: November 26, 2024

Learn how inadequate analytics impact your testing processes and discover strategies to overcome reporting challenges. Elevate your QA efficiency with actionable solutions for accurate insights, smarter decisions, and enhanced QA outcomes.

Optimal Methods and Metrics for LLM Evaluation and Testing

Optimal Methods and Metrics for LLM Evaluation and Testing

Publish Date: June 12, 2024

Discover key strategies for Large Language Model (LLM) testing, including continuous monitoring, human assessments, and effective use of MLOps. Learn to choose the right tools for comprehensive LLM evaluation and enhance model reliability with QASource.

Understanding Software Quality Metrics with Manual and Automated Testing

Understanding Software Quality Metrics with Manual and Automated Testing

Publish Date: August 29, 2019

Quality is the true measure of product success. Poor user experience or application performance negates any advantages you achieve in delivery speed or production cost. Put simply, if it does not work, it is not worth producing. It is, therefore, critical to our product success that we can accurately measure and track test results to ensure our testing is delivering against our business goals. Understanding software quality metrics, especially in automated testing, helps us identify what is working well and what needs improvement.

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Our bloggers are the test management experts at QASource. They are executives, QA managers, team leads, and testing practitioners. Their combined experience exceeds 100 years and they know how to optimize QA efforts in a variety of industries, domains, tools, and technologies.