Predicting defects in SAP Java code: An experience report

Which components of a large software system are the most defect-prone? In a study on a large SAP Java system, we evaluated and compared a number of defect predictors, based on code features such as complexity metrics, static error detectors, change frequency, or component imports, thus replicating a number of earlier case studies in an industrial context. We found the overall predictive power to be lower than expected; still, the resulting regression models successfully predicted 50–60% of the 20% most defectprone components.

• Type: Conference
• Year: 2009
• Where: ICSE
• Authors: Tilman Holschuh, Markus Pauser, Kim Herzig, Thomas Zimmermann, Rahul Premraj, Andreas Zeller
• Keywords: ICSE 2009, Large Sap Java, Overall Predictive Power, Software Engineering, Static Error Detectors