Authors: Adriana Marotta, Diego Vallespir, Jose Ignacio Panach, María Carolina Valverde
Tags: 2014, conceptual modeling
Data collection and analysis are key artifacts in any software engineering experiment. However, these data might contain errors. We propose a Data Quality model specific to data obtained from software engineering experiments, which provides a framework for analyzing and improving these data. We apply the model to two controlled experiments, which results in the discovery of data quality problems that need to be addressed. We conclude that data quality issues have to be considered before obtaining the experimental results.Read the full paper here: https://link.springer.com/chapter/10.1007/978-3-319-12256-4_18
