NDLI: Predicting fault-prone modules with case-based reasoning

Content Provider	IEEE Xplore Digital Library
Author	Khoshgoftaar, T.M. Ganesan, K. Allen, E.B. Ross, F.D. Munikoti, R. Goel, N. Nandi, A.
Copyright Year	1997
Description	Author affiliation: Florida Atlantic Univ., Boca Raton, FL, USA (Khoshgoftaar, T.M.)
Abstract	Software quality classification models seek to predict quality factors such as whether a module will be fault prone, or not. Case based reasoning (CBR) is a modeling technique that seeks to answer new questions by identifying similar "cases" from the past. When applied to software reliability, the working hypothesis of our approach is this: a module currently under development is probably fault prone if a module with similar product and process attributes in an earlier release was fault prone. The contribution of the paper is application of case based reasoning to software quality modeling. To the best of our knowledge, this is the first time that case based reasoning has been used to identify fault prone modules. A case study illustrates our approach and provides evidence that case based reasoning can be the basis for useful software quality classification models that are competitive with discriminant models. The case study revisits data from a previously published nonparametric discriminant analysis study. The Type II misclassification rate of the CBR model was substantially better than that of the discriminant model. Although the Type I misclassification rate was slightly greater and the overall misclassification rate was only slightly less, the CBR model was preferred when costs of misclassification were considered.
Starting Page	27
Ending Page	35
File Size	789366
Page Count	9
File Format	PDF
ISBN	0818681209
DOI	10.1109/ISSRE.1997.630845
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1997-11-02
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Software quality Software engineering Predictive models Q factor Software reliability Fault diagnosis History Laboratories Costs Time measurement
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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