Using Developer Information as a Factor for Fault Prediction

Authors:
Elaine J. Weyuker;Thomas J. Ostrand;Robert M. Bell
Affiliations:
AT&T Labs--Research, USA;AT&T Labs--Research, USA;AT&T Labs--Research, USA
Venue:
PROMISE '07 Proceedings of the Third International Workshop on Predictor Models in Software Engineering
Year:
2007

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Abstract

We have been investigating different prediction models to identify which files of a large multi-release industrial software system are most likely to contain the largest numbers of faults in the next release. To make predictions we considered a number of different file characteristics and change information about the files, and have built fully-automatable models that do not require that the user have any statistical expertise. We now consider the effect of adding developer information as a prediction factor and assess the extent to which this affects the quality of the predictions.