[ACM Press Proceeding of the 28th international conference - Shanghai, China (2006.05.20-2006.05.28)] Proceeding of the 28th international conference on Software engineering - ICSE '06 - Mining metrics to predict component failures

✍ Scribed by Nagappan, Nachiappan; Ball, Thomas; Zeller, Andreas

• Book ID: 121242015
• Publisher: ACM Press
• Year: 2006
• Tongue: English
• Weight: 219 KB
• Category: Article
• ISBN-13: 9781595933751
• DOI: 10.1145/1134285.1134349

✦ Synopsis

What is it that makes software fail? In an empirical study of the post-release defect history of five Microsoft software systems, we found that failure-prone software entities are statistically correlated with code complexity measures. However, there is no single set of complexity metrics that could act as a universally best defect predictor. Using principal component analysis on the code metrics, we built regression models that accurately predict the likelihood of post-release defects for new entities. The approach can easily be generalized to arbitrary projects; in particular, predictors obtained from one project can also be significant for new, similar projects.