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Issue No.03 - May/June (2008 vol.34)
pp: 336-356
Syed W. Haider , The University of Texas at Dallas, Dallas
João W. Cangussu , The University of Texas at Dallas, Dallas
Kendra M.L. Cooper , The University of Texas at Dallas, Dallas
Ram Dantu , University of North Texas, Denton
Syed Haider , The University of Texas at Dallas, Dallas
ABSTRACT
An accurate prediction of the number of defects in a software product during system testing contributes not only to the management of the system testing process but also to the estimation of the product's required maintenance. Here, a new approach called ED^3M is presented that computes an estimate of the total number of defects in an ongoing testing process. ED^3M is based on estimation theory. Unlike many existing approaches the technique presented here does not depend on historical data from previous projects or any assumptions about the requirements and/or testers' productivity. It is a completely automated approach that relies only on the data collected during an ongoing testing process. This is a key advantage of the ED^3M approach, as it makes it widely applicable in different testing environments. Here, the ED^3M approach has been evaluated using five data sets from large industrial projects and two data sets from the literature. In addition, a performance analysis has been conducted using simulated data sets to explore its behavior using different models for the input data. The results are very promising; they indicate the ED^3M approach provides accurate estimates with as fast or better convergence time in comparison to well-known alternative techniques, while only using defect data as the input.
INDEX TERMS
Statistical methods, Testing and Debugging, Metrics/Measurement, Defect prediction, system testing, estimation theory
CITATION
Syed W. Haider, João W. Cangussu, Kendra M.L. Cooper, Ram Dantu, Syed Haider, "Estimation of Defects Based on Defect Decay Model: ED^{3}M", IEEE Transactions on Software Engineering, vol.34, no. 3, pp. 336-356, May/June 2008, doi:10.1109/TSE.2008.23
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