GITNUX MARKETDATA REPORT 2023

Must-Know Quality Assurance Metrics

Last Updated: October 31, 2023

Written & Summarized by: Jannik Lindner

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Highlights: The Most Important Quality Assurance Metrics

1. Defect Density
2. Test Case Execution Rate
3. Test Case Pass Rate
4. Test Case Coverage
5. Requirement Coverage
6. Defect Age
7. Defect Resolution Time
8. Defect Severity
9. Defect Removal Efficiency (DRE)
10. Defect Root Cause Analysis (RCA)
11. Test Effort
12. Code Quality
13. Code Review Coverage
14. Customer Reported Defects
15. Customer Satisfaction

Quality Assurance Metrics: Our Guide

In today’s technology-driven world, Quality Assurance (QA) has become a fundamental pillar for any successful software project. Therefore, understanding and implementing effective Quality Assurance metrics has gained paramount importance. This blog post will delve into the must-know QA metrics that can enhance your software development process, ensuring quality, efficiency, and customer satisfaction.

Defect Density

This metric calculates the number of defects identified in the software during a specific period, divided by the size of the software

Throughput

The number of requests an application can handle per unit time. Higher throughput indicates a more efficient application that can handle increased load

Error Rate

The percentage of requests resulting in errors. Lower error rates indicate a more stable and reliable application.

Apdex Score

A numerical measure that evaluates an application’s performance based on user satisfaction

CPU Usage

The percentage of the processor’s capacity used by an application. This metric indicates the efficiency of the application and its resource consumption

Memory Usage

The amount of system memory allocated to and used by an application. This metric also indicates the efficiency of the application and its resource consumption.

Disk Usage

The amount of disk space used by an application for storage and caching. Minimizing disk usage can help ensure the application’s scalability and efficiency

Network Latency

The time it takes for a request to travel between the client and server or between different servers in an application.

Cache Hit Ratio

The percentage of data requests that are served from the cache instead of being fetched from the database or other sources.

Database Query Performance

The time it takes to execute specific database queries, as well as the throughput of running queries within the application.

Garbage Collection

The frequency and duration of garbage collection events in an application, which are responsible for freeing up memory from unused objects.

Thread And Connection Pool Usage

The count of active threads and connections in an app. Monitoring aids bottleneck detection, concurrency optimization, and maintaining responsiveness during heavy loads

Request Size

Incoming request size in bytes, including headers, payload, and metadata. Monitoring aids request handling and boosts app performance.

Response Size

Outgoing response size in bytes, including headers, content, and metadata. Monitoring aids in detecting data handling issues and optimization

Availability

Application uptime percentage is crucial for a reliable user experience

Frequently Asked Questions

What are Quality Assurance Metrics?

Quality Assurance Metrics are quantifiable tools and indicators used to measure and evaluate the efficiency, effectiveness, and performance of a product, process, or team in a software development or testing environment.

Why are Quality Assurance Metrics important?

Quality Assurance Metrics are important because they help organizations track progress, identify problem areas, and take necessary actions to improve their products and processes. These metrics also provide a standard for evaluating performance, ensuring efficiency, and keeping stakeholders informed about the overall quality of the product.

What are some examples of Quality Assurance Metrics?

Examples of Quality Assurance Metrics include test coverage, defect density, defect detection percentage, defect resolution time, and team productivity. These metrics provide insights into the quality of the product, the efficiency of the testing process, and the effectiveness of the team involved in the process.

How can Quality Assurance Metrics be used to improve a product or process?

Quality Assurance Metrics can be used to identify areas where improvement is needed, uncover trends that may not be immediately evident, and prioritize issues. By setting realistic goals and using these metrics as a measuring stick, organizations can implement strategies to improve their products or processes and ensure they meet or exceed the required quality standards.

How often should Quality Assurance Metrics be reviewed and updated?

Quality Assurance Metrics should be reviewed and updated regularly, typically on a weekly or monthly basis, depending on the organization’s needs and the specific metric. Regular reviews help ensure alignment with project goals, provide insights into potential risks, and allow for timely corrective action if required.

How we write these articles

We have not conducted any studies ourselves. Our article provides a summary of all the statistics and studies available at the time of writing. We are solely presenting a summary, not expressing our own opinion. We have collected all statistics within our internal database. In some cases, we use Artificial Intelligence for formulating the statistics. The articles are updated regularly. See our Editorial Guidelines.

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