Peer code review is key to ensuring the absence of software defects. To reduce review costs, software developers adopt code convention checking tools that automatically identify maintainability issues in source code. However, these tools do not always address the maintainability issue for a particular project. The goal of this study is to understand how code review fixes conditional statement issues, which are the most frequent changes in software development. We conduct an empirical study to understand if-statement changes through code review. Using review requests in the Qt and OpenStack projects, we analyze changes of the if-conditional statements that are (1) requested to be reviewed, and are (2) revised through code review. We find the most frequently changed symbols are “( )”, “.”, and “!”. We also find project-specific fixing patterns for improving code readability by association rule mining. For example “!” operator is frequently replaced with a function call. These rules are useful for improving a coding convention checker tailored for the projects.

Adherence to coding conventions during the code production stage of software development is essential. Benefits include enabling programmers to quickly understand the context of shared code, communicate with one another in a consistent manner, and easily maintain the source code at low costs. In reality, however, programmers tend to doubt or ignore the degree to which the quality of their code is affected by adherence to these guidelines. This paper addresses research questions such as “Do violations of coding conventions affect the readability of the produced code?”, “What kinds of coding violations reduce code readability?”, and “How much do variable factors such as developer experience, project size, team size, and project maturity influence coding violations?” To respond to these research questions, we explored 210 open-source Java projects with 117 coding conventions from the Sun standard checklist. We believe our findings and the analysis approach used in the paper will encourage programmers and QA managers to develop their own customized and effective coding style guidelines.