  Background. Pull requests are a common practice for contributing and
reviewing contributions, and are employed both in open-source and industrial
contexts. One of the main goals of code reviews is to find defects in the code,
allowing project maintainers to easily integrate external contributions into a
project and discuss the code contributions. Objective. The goal of this paper
is to understand whether code quality is actually considered when pull requests
are accepted. Specifically, we aim at understanding whether code quality issues
such as code smells, antipatterns, and coding style violations in the pull
request code affect the chance of its acceptance when reviewed by a maintainer
of the project. Method. We conducted a case study among 28 Java open-source
projects, analyzing the presence of 4.7 M code quality issues in 36 K pull
requests. We analyzed further correlations by applying Logistic Regression and
seven machine learning techniques (Decision Tree, Random Forest, Extremely
Randomized Trees, AdaBoost, Gradient Boosting, XGBoost). Results. Unexpectedly,
code quality turned out not to affect the acceptance of a pull request at all.
As suggested by other works, other factors such as the reputation of the
maintainer and the importance of the feature delivered might be more important
than code quality in terms of pull request acceptance. Conclusions. Researchers
already investigated the influence of the developers' reputation and the pull
request acceptance. This is the first work investigating if quality of the code
in pull requests affects the acceptance of the pull request or not. We
recommend that researchers further investigate this topic to understand if
different measures or different tools could provide some useful measures.
