Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/68078
Title: A comparison between software design and code metrics for the prediction of software fault content
Authors: Zhao, M.
Wohlin, C.
Ohlsson, N.
Xie, M. 
Keywords: Correlation analysis
Fault prediction
Metric selection
Regression analysis
Software metrics
Issue Date: 1-Dec-1998
Source: Zhao, M.,Wohlin, C.,Ohlsson, N.,Xie, M. (1998-12-01). A comparison between software design and code metrics for the prediction of software fault content. Information and Software Technology 40 (14) : 801-809. ScholarBank@NUS Repository.
Abstract: Software metrics play an important role in measuring the quality of software. It is desirable to predict the quality of software as early as possible, and hence metrics have to be collected early as well. This raises a number of questions that has not been fully answered. In this paper we discuss, prediction of fault content and try to answer what type of metrics should be collected, to what extent design metrics can be used for prediction, and to what degree prediction accuracy can be improved if code metrics are included. Based on a data set collected from a real project, we found that both design and code metrics are correlated with the number of faults. When the metrics are used to build prediction models of the number of faults, the design metrics are as good as the code metrics, little improvement can be achieved if both design metrics and code metrics are used to model the relationship between the number of faults and the software metrics. The empirical results from this study indicate that the structural properties of the software influencing the fault content is established before the coding phase. © 1998 Elsevier Science B.V. All rights reserved.
Source Title: Information and Software Technology
URI: http://scholarbank.nus.edu.sg/handle/10635/68078
ISSN: 09505849
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

Page view(s)

35
checked on Dec 15, 2017

Google ScholarTM

Check


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.