%0 Conference Paper %1 nagappan06 %A Nagappan, Nachiappan %A Ball, Thomas %A Zeller, Andreas %B International Conference on Software engineering %C Shanghai, China %D 2006 %I ACM %K imported %P 452--461 %T Mining metrics to predict component failures %U http://doi.acm.org/10.1145/1134285.1134349 %X 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. %@ 1-59593-375-1

@inproceedings{nagappan06, abstract = {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.}, added-at = {2007-11-23T17:50:43.000+0100}, address = {Shanghai, China}, author = {Nagappan, Nachiappan and Ball, Thomas and Zeller, Andreas}, biburl = {https://www.bibsonomy.org/bibtex/237bb9df82b14e322d859d4f180d1c861/neilernst}, booktitle = {International Conference on Software engineering}, description = {Mining metrics to predict component failures}, interhash = {2cbfae1d8dd1aa5a28e42877aec75f32}, intrahash = {37bb9df82b14e322d859d4f180d1c861}, isbn = {1-59593-375-1}, keywords = {imported}, location = {Shanghai, China}, month = {September}, pages = {452--461}, publisher = {ACM}, timestamp = {2007-11-23T17:50:43.000+0100}, title = {Mining metrics to predict component failures}, url = {http://doi.acm.org/10.1145/1134285.1134349}, year = 2006 }