Code Understandability
The dataset accompanying the paper "Demystifying and Assessing Code Understandability in Java Decompilation" is structured to facilitate a comprehensive analysis of code understandability in Java decompilation. The data is organized into two main directories: data/original and data/testset, representing the original dataset and the test set, respectively. Each directory encompasses three components. First, the code directory contains experimental data, including source code and corresponding decompiled code produced by three decompilers: CFR, Fernflower, and Jadx.
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This dataset is the result of test case and developer metrics extraction from Honfi's experiment in https://zenodo.org/record/2596044#.Xnm4sS2B1QJ
The detail of test case extraction is attached.
It contained 20 metrics from the generated test case and six metrics from the profile of developers. 26 metrics act as independent variable. There are two dependent variables : ABU (Actual Binary Understandability) and TAU (Timed Actual Understandability).
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Understanding software is an inherent requirement for many maintenance and evolution tasks. Without a thorough understanding of the code, developers would not be able to fix bugs or add new features timely. Measuring code understandability might be useful to guide developers in writing better code, and could also help in estimating the effort required to modify code components. Unfortunately, there are no metrics designed to assess the understandability of code snippets.
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