Data Collection in a Process-Sensitive Software Engineering Environment

All software projects are experiments in the sense of the scientific method because the outcomes are not known in advance, theories and hypotheses may be tested in the project empirically, and data must be collected and analyzed. Empirical data allows us to characterize projects, gauge improvements in an environment, and reason about the value of new technologies. This paper discusses our ideas about practical support for collecting empirical data using a process-sensitive software engineering environment