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Identifying and Characterizing Change-prone Classes in Two Large-scale Open-source Products by A. Güneş Koru; Hongfang Liu is a Computer Science article available to read on EtoBox.

What is Identifying and Characterizing Change-prone Classes in Two Large-scale Open-source Products about?

Developing and maintaining open-source software has become an important source of profit for many companies. Change-prone classes in open-source products increase project costs by requiring developers to spend effort and time. Identifying and characterizing change-prone classes can enable developers to focus timely preventive actions, for example, peer-reviews and inspections, on the classes with similar characteristics in the future releases or products. In this study, we collected a set of static metrics and change data at class level from two open-source projects, KOffice and Mozilla. Using these data, we first tested and validated Pareto's Law which implies that a great majority (around 80%) of change is rooted in a small proportion (around 20%) of classes. Then, we identified and characterized the change-prone classes in the two products by producing tree-based models. In addition, using tree-based models, we suggested a prioritization strategy to use project resources for focused preventive actions in an efficient manner. Our empirical results showed that this strategy was effective for prioritization purposes. This study should provide useful guidance to practitioners involv

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Author

A. Güneş Koru; Hongfang Liu

Publisher

Elsevier Science; Elsevier ; Elsevier BV (ISSN 0164-1212)

Published

2007

Language

EN

Field

Computer Science (Physical Sciences)