Software errors and complexity: an empirical investigation0
Communications of the ACM
The Detection of Fault-Prone Programs
IEEE Transactions on Software Engineering
Predicting Fault Incidence Using Software Change History
IEEE Transactions on Software Engineering
Does Code Decay? Assessing the Evidence from Change Management Data
IEEE Transactions on Software Engineering
The distribution of faults in a large industrial software system
ISSTA '02 Proceedings of the 2002 ACM SIGSOFT international symposium on Software testing and analysis
An empirical evaluation of fault-proneness models
Proceedings of the 24th International Conference on Software Engineering
Reexamining the Fault Density-Component Size Connection
IEEE Software
A Metrics Suite for Object Oriented Design
IEEE Transactions on Software Engineering
Quantitative Analysis of Faults and Failures in a Complex Software System
IEEE Transactions on Software Engineering
An Empirical Analysis of Fault Persistence Through Software Releases
ISESE '03 Proceedings of the 2003 International Symposium on Empirical Software Engineering
ISSTA '04 Proceedings of the 2004 ACM SIGSOFT international symposium on Software testing and analysis
Robust Prediction of Fault-Proneness by Random Forests
ISSRE '04 Proceedings of the 15th International Symposium on Software Reliability Engineering
Predicting the Location and Number of Faults in Large Software Systems
IEEE Transactions on Software Engineering
Looking for bugs in all the right places
Proceedings of the 2006 international symposium on Software testing and analysis
Predicting fault-prone components in a java legacy system
Proceedings of the 2006 ACM/IEEE international symposium on Empirical software engineering
Automating algorithms for the identification of fault-prone files
Proceedings of the 2007 international symposium on Software testing and analysis
How to measure success of fault prediction models
Fourth international workshop on Software quality assurance: in conjunction with the 6th ESEC/FSE joint meeting
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Although this is a talk about the design of predictive models to determine where faults are likely to be in the next release of a large software system, the primary focus of the talk is the process that was followed when doing this type of software engineering research. We follow the project from problem inception (cradle) to productization (grave), describing each of the intermediate stages to try to give a picture of why such research takes so long, and also why it is necessary to perform each of the steps.