Software reliability: measurement, prediction, application
Software reliability: measurement, prediction, application
Predicting Fault Incidence Using Software Change History
IEEE Transactions on Software Engineering
A non-parametric approach to software reliability: Research Articles
Applied Stochastic Models in Business and Industry - Reliability
Early Software Reliability Prediction with ANN Models
PRDC '06 Proceedings of the 12th Pacific Rim International Symposium on Dependable Computing
Predicting Defects for Eclipse
PROMISE '07 Proceedings of the Third International Workshop on Predictor Models in Software Engineering
EvoJava: a tool for measuring evolving software
ACSC '11 Proceedings of the Thirty-Fourth Australasian Computer Science Conference - Volume 113
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Code repositories and bug databases contain valuable information about the process of software development. Typical studies correlate code properties with the number of faults in a software module to find error-prone modules. However, many studies do not regard the occurrence of faults over time, although the time information can be retrieved from bug databases. In order to overcome this problem, we suggest the application of survival analysis models, which are used in biostatistics and can handle time-dependent data. Because a large amount of raw data has to be evaluated statistically, we further discuss the automated retrieval and pre-processing of raw data from code repositories and bug databases.