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ICTAI
2002
IEEE

Machine Learning for Software Engineering: Case Studies in Software Reuse

14 years 3 months ago
Machine Learning for Software Engineering: Case Studies in Software Reuse
There are many machine learning algorithms currently available. In the 21st century, the problem no longer lies in writing the learner, but in choosing which learners to run on a given data set. In this paper, we argue that the final choice of learners should not be exclusive; in fact, there are distinct advantages in running data sets through multiple learners. To illustrate our point, we perform a case study on a reuse data set using three different styles of learners: association rule, decision tree induction, and treatment. Software reuse is a topic of avid debate in the professional and academic arena; it has proven that it can be both a blessing and a curse. Although there is much debate over where and when reuse should be instituted into a project, our learners found some procedures which should significantly improve the odds of a reuse program succeeding.
Justin S. Di Stefano, Tim Menzies
Added 15 Jul 2010
Updated 15 Jul 2010
Type Conference
Year 2002
Where ICTAI
Authors Justin S. Di Stefano, Tim Menzies
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