Change-proneness datasets

Citation Author(s):
Hadeel
Alsolai
Princess Nourah Bint Abdulrahman University, Riyadh, Saudi Arabia
Submitted by:
Hadeel Alsolai
Last updated:
Sun, 01/30/2022 - 14:07
DOI:
10.21227/m4kx-j760
License:
0
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Abstract 

I performed pre-processing methods on refactoring datasets proposed in (Empirical evaluation of software maintainability based on a manually validated refactoring dataset) by PéterHegedűs et al. The new version of these datasets support Change-proneness study.

Instructions: 

The independent variables are numeric and include 125 metrics, which can be grouped into ten categories as follows: cohesion, complexity, coupling, documentation, inheritance, size, code duplication, warning, rules and refactoring. the dependent variable is Boolean ( True or False) and can be used to predict Change prone.

The datasets can be used to apply different machine learning models using different evaluation measures for classification problem.

 

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