1st international workshop on in process software engineering measurement and analysis (isema 2007)
Improving the software engineering development process requires collection of data, but collection of data interferes with how developers work. At present, most of the software engineering tools, data collection, and analysis techniques available use manual data collection, despite known problems with reliability, correctness, and timeliness of the data. To overcome such limitations and reduce interference with the development process, software engineering researchers must develop tools and data analysis techniques that collect data without human interactions. Such tools produce very detailed and extensive data, but lack the filtering and classification that humans perform on manually collected data. This unfiltered data requires the development of new analysis techniques and new prediction models to use it effectively. This workshop focuses on defining the research challenges created by in process software measurement and analysis of the software development process using tools that do not affect or modify the process but extract data automatically from it.
non-invasive data collection empirical software engineering