What measuring technique uses a representative set of data to evaluate performance?

The technique that uses a representative set of data to evaluate performance is benchmarking. Benchmarking involves comparing the performance of a system, application, or process against a known standard or best practice. This is typically done by running tests on a sample of data that effectively reflects typical usage scenarios in order to gauge how well the system performs under certain conditions.

By using a representative set of data, benchmarking allows developers and organizations to identify areas for improvement, set performance targets, and ensure that their systems can meet business needs or user expectations. This method is essential for establishing quality metrics, enabling informed decisions on enhancements, and tracking performance over time.

In contrast, modeling focuses on creating abstract representations of systems to understand or predict their behavior, while simulating involves running a model to replicate the operation of a system under various conditions, often including scenarios that may not have been encountered before. Profiling, on the other hand, is concerned with analyzing the performance of individual components within a system, such as tracking resource usage or identifying bottlenecks. While all these techniques are valuable in their contexts, benchmarking specifically emphasizes the evaluation of overall performance against established criteria or standards using representative data.