Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Prioritizing documentation effort: Can we do better?   Code documentations are essential for software quality assurance, but due to
time or economic pressures, code developers are often unable to write documents
for all modules in a project. Recently, a supervised artificial neural network
(ANN) approach is proposed to prioritize important modules for documentation
effort. However, as a supervised approach, there is a need to use labeled
training data to train the prediction model, which may not be easy to obtain in
practice. Furthermore, it is unclear whether the ANN approach is generalizable,
as it is only evaluated on several small data sets. In this paper, we propose
an unsupervised approach based on PageRank to prioritize documentation effort.
This approach identifies "important" modules only based on the dependence
relationships between modules in a project. As a result, the PageRank approach
does not need any training data to build the prediction model. In order to
evaluate the effectiveness of the PageRank approach, we use six additional
large data sets to conduct the experiments in addition to the same data sets
collected from open-source projects as used in prior studies. The experimental
results show that the PageRank approach is superior to the state-of-the-art ANN
approach in prioritizing important modules for documentation effort. In
particular, due to the simplicity and effectiveness, we advocate that the
PageRank approach should be used as an easy-to-implement baseline in future
research on documentation effort prioritization, and any new approach should be
compared with it to demonstrate its effectiveness.

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The categories of this paper are: hep-th
36
The categories of this paper are: cmp-lg
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The categories of this paper are: gr-qc
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The categories of this paper are: bayes-an
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The categories of this paper are: hep-ex
12
The categories of this paper are: nucl-th
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The categories of this paper are: dg-ga
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The categories of this paper are: chao-dyn
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The categories of this paper are: quant-ph
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The categories of this paper are: patt-sol
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The categories of this paper are: comp-gas
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The categories of this paper are: funct-an
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The categories of this paper are: econ
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The categories of this paper are: math-ph
37
The categories of this paper are: supr-con
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The categories of this paper are: physics