2006
DOI: 10.1016/j.infsof.2005.03.002
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An application of Bayesian network for predicting object-oriented software maintainability

Abstract: The Department of Information Science is one of six departments that make up the School of Business at the University of Otago. The department offers courses of study leading to a major in Information Science within the BCom, BA and BSc degrees. In addition to undergraduate teaching, the department is also strongly involved in postgraduate research programmes leading to MCom, MA, MSc and PhD degrees. Research projects in spatial information processing, connectionist-based information systems, software engineer… Show more

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Cited by 154 publications
(106 citation statements)
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References 31 publications
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“…The use of function points are proposed for estimating the effort of software maintenance projects [1]. Bayesian Networks are also used in Software Maintenance [26]. Van Koten and Gray [26] use Bayesian Networks to predict the maintainability measured as the change in software lines of code between subsequent releases.…”
Section: Related Workmentioning
confidence: 99%
See 2 more Smart Citations
“…The use of function points are proposed for estimating the effort of software maintenance projects [1]. Bayesian Networks are also used in Software Maintenance [26]. Van Koten and Gray [26] use Bayesian Networks to predict the maintainability measured as the change in software lines of code between subsequent releases.…”
Section: Related Workmentioning
confidence: 99%
“…Bayesian Networks are also used in Software Maintenance [26]. Van Koten and Gray [26] use Bayesian Networks to predict the maintainability measured as the change in software lines of code between subsequent releases. The results are improved compared to regression models.…”
Section: Related Workmentioning
confidence: 99%
See 1 more Smart Citation
“…[6], code smells [7], design patterns and [8] evolution metrics [9,10]. In terms of the techniques, different machine learning approaches have been used, such as Bayesian networks [11], neural networks [12], multivariate regression [1] and ensemble methods [5]. A typical prediction model based on machine learning is designed by learning from a historical labeled dataset in a supervised way.…”
Section: Introductionmentioning
confidence: 99%
“…This effort is measured by means of the time spent on performing a maintenance task [6], [22], the changes performed [21], [23], [24], or the maintainability index (MI) [25]. The changes made in the code is in most cases approximated by number of lines of code changed.…”
Section: Introductionmentioning
confidence: 99%