id: Arisholm.2006.4
authors: Erik Arisholm and Lionel Claude L. Briand
title: Predicting Fault-prone Components in a Java Legacy System
publication_year: 2006
abstract: This paper reports on the construction and validation of fault-proneness prediction models in the context of an object-oriented, evolving, legacy system. The goal is to help QA engineers focus their limited verification resources on parts of the system likely to contain faults. A number of measures including code quality, class structure, changes in class structure, and the history of class-level changes and faults are included as candidate predictors of class fault-proneness. A cross-validated classification analysis shows that the obtained model has less than 20% of false positives and false negatives, respectively. However, as shown in this paper, statistics regarding the classification accuracy tend to inflate the potential usefulness of the fault-proneness prediction models. We thus propose a simple and pragmatic methodology for assessing the cost-effectiveness of the predictions to focus verification effort. On the basis of the cost-effectiveness analysis we show that change and fault data from previous releases is paramount to developing a practically useful prediction model. When our model is applied to predict faults in a new release, the estimated potential savings in verification effort is about 29%. In contrast, the estimated savings in verification effort drops to 0% when history data is not included.
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booktitle: 5th ACM-IEEE International Symposium on Empirical Software Engineering (ISESE), Rio de Janeiro, Brazil, September 21-22
editor: Maldonado, Mendes & Wohlin
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pages: 8-17
publisher: ACM
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isbn: 1-59593-218-6
keywords: ()
publication_month: September
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publication_state: Published
simula_ou: [<Department at /simula/department/certus>, <Department at /simula/research/approve>]
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category: Conference
from_date: 2006/09/21 00:00:00 GMT+2
to_date: 2006/09/22 00:00:00 GMT+2