Which of the following is a key metric for evaluating testing effectiveness?

Defect density serves as a key metric for evaluating testing effectiveness as it provides a quantitative measure of how many defects are found during testing in relation to the size of the software product—typically measured in lines of code or function points. This metric allows testing teams to assess the quality of the software product by identifying the number of faults in comparison to its size, helping to gauge the testing process's efficiency.

When defect density is low, it often indicates that the software is high quality and that the testing process is effective in uncovering issues during development. Conversely, a high defect density may suggest problems in the code or that the testing activities were not thorough, prompting the need for a review of testing strategies and practices. This focus on the ratio between defects and product size makes defect density a significant indicator for stakeholders regarding the actual state of quality and the effectiveness of testing efforts.

In contrast, while brand recognition, user feedback, and the cost of testing resources can provide valuable insights into a product's market position and operational efficiency, they do not directly measure the effectiveness of the testing process itself in identifying and resolving defects within the software.