# A Survey of Automatic Generation of Source Code Comments: Algorithms and Techniques

## TL;DR

This survey reviews algorithms and techniques for automatically generating source code comments, discussing challenges, classifications, quality assessment, and future research directions to improve software readability and maintenance.

## Contribution

It provides a comprehensive classification and analysis of existing automatic code commenting methods, highlighting their strengths, weaknesses, and future research avenues.

## Key findings

- Classifies algorithms into categories with design principles
- Analyzes strengths and weaknesses of different approaches
- Summarizes quality assessment methods for generated comments

## Abstract

As an integral part of source code files, code comments help improve program readability and comprehension. However, developers sometimes do not comment on their program code adequately due to the incurred extra efforts, lack of relevant knowledge, unawareness of the importance of code commenting or some other factors. As a result, code comments can be inadequate, absent or even mismatched with source code, which affects the understanding, reusing and the maintenance of software. To solve these problems of code comments, researchers have been concerned with generating code comments automatically. In this work, we aim at conducting a survey of automatic code commenting researches. First, we generally analyze the challenges and research framework of automatic generation of program comments. Second, we present the classification of representative algorithms, the design principles, strengths and weaknesses of each category of algorithms. Meanwhile, we also provide an overview of the quality assessment of the generated comments. Finally, we summarize some future directions for advancing the techniques of automatic generation of code comments and the quality assessment of comments.