Initial evaluation of data quality in a TSP software engineering project data repository

To meet critical business challenges, software development teams need data to effectively manage product quality, cost, and schedule. The Team Software ProcessSM (TSPSM) provides a framework that teams use to collect software process data in real time, using a defined disciplined process. This data holds promise for use in software engineering research. We combined data from 109 industrial projects into a database to support performance benchmarking and model development. But is the data of sufficient quality to draw conclusions? We applied various tests and techniques to identify data anomalies that affect the quality of the data in several dimensions. In this paper, we report some initial results of our analysis, describing the amount and the rates of identified anomalies and suspect data, including incorrectness, inconsistency, and credibility. To illustrate the types of data available for analysis, we provide three examples. The preliminary results of this empirical study suggest that some aspects of the data quality are good and the data are generally credible, but size data are often missing.