Evaluating software development by analysis of changes: The data from the software engineering laboratory

Abstract

An effective data collection methodology for evaluating software development methodologies was applied to four different software development projects. Goals of the data collection included characterizing changes and errors, characterizing projects and programmers, identifying effective error detection and correction techniques, and investigating ripple effects. The data collected consisted of changes (including error corrections) made to the software after code was written and baselined, but before testing began. Data collection and validation were concurrent with software development. Changes reported were verified by interviews with programmers.