Investigating ARIMA models of software system quality |
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Authors: | Taghi M. Khoshgoftaar Robert M. Szabo |
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Affiliation: | (1) Department of Computer Science and Engineering, Florida Atlantic University, 33431 Boca Raton, FL, USA;(2) IBM Corporation, 1000 N.W. 51 Street, 33429 Boca Raton, FL, USA |
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Abstract: | In this paper, we investigate how to incorporate program complexity measures with a software quality model. We collect software complexity metrics and fault counts from each build during the testing phase of a large commercial software system. Though the data are limited in quantity, we are able to predict the number of faults in the next build. The technique we used is called times series analysis and forecasting. The methodology assumes that future predictions are based on the history of past observations. We will show that the combined complexity quality model is an improvement over the simpler quality only model. Finally, we explore how the testing process used in this development may be improved by using these predictions and suggest areas for future research. |
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Keywords: | predictive quality software complexity metrics software quality metrics software testing time series analysis |
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