Parameter Description Generation with the Code Parameter Flow

Abstract

Prior study shows that comprehending parameters can help developers understand the code’s critical information (e.g., the argument) and enhance the comprehension of the functionality. However, commenting parameter is often ignored in practice. For example, a statistic of 18 popular open-source projects shows the ratio of methods with one or more parameters but lacking "@param" comment ranges from 31% to 97%, indicating the necessity of parameter comments.To fill this gap, we propose ParamDesGen to generate a descriptive code comment (description) for each parameter given a method with one or more formal parameters. ParamDesGen consists of (1) a code analysis component to identify the Parameter Flow and extract "parameter-related code parts" and (2) a machine-learning component to generate parameter comments. We build a large-scale dataset for the task and perform experiments on it to evaluate ParamDesGen. The evaluation results show that the proposed approach substantially outperforms the baselines in terms of BLEU-4 scores (22.54 absolute improvement and 138.79% relative improvement) and ROUGE-L scores (3.12 absolute improvement and 5.90% relative improvement). We further perform ablation experiments to prove the effectiveness of the Parameter Flow.