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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 newdoi:10.1145/1134285.1134349 dblp:conf/icse/NagappanBZ06 fatcat:5z7xsgy2tjhrtpdly6mpohbdwm