| Abstract | A large number of software product metrics 1 have been proposed in software engineering. Product metrics quantitatively characterize some aspect of the structure of a software product, such as a requirements specification, a design, or source code. They are also commonly collectively known as complexity metrics. While many of these metrics are based on good ideas about what is important to measure in software to capture its complexity, it is still necessary to systematically validate them. Recent software engineering literature has reflected a concern for the quality of methods to validate software product metrics (e.g., see [38][80][106]). This concern is driven, at least partially, by a recognition that: (i) common practices for the validation of software engineering metrics are not acceptable on scientific grounds, and (ii) valid measures are essential for effective software project management and sound empirical research. For example, in a recent paper [80], the authors write: "Unless the software measurement community can agree on a valid, consistent, and comprehensive theory of measurement validation, we have no scientific basis for the discipline of software measurement, a situation potentially disasterous for both practice and research." Therefore, to have confidence in the utility of the many metrics that are proposed from research labs, it is crucial that they are validated. |
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