Code Summarization

Abstract

The goal of code summarizing, an emerging topic, is to automatically create human-readable summaries of source code.Understanding and maintaining huge codebases for developers becomes more difficult as software systems become more complicated.By utilizing natural language processing (NLP) and machine learning techniques, code summarization aims to close this gap by automatically producing clear and detailed descriptions of code parts, such as functions or complete programs.Advanced deep learning models may provide summaries that are correct and relevant to the context by examining the syntax and semantics of the code, identifying significant components, and learning from enormous datasets of code-summary pairings.These descriptions help engineers collaborate and understand the code, which can improve output and software quality.The usefulness and efficiency of code summarization approaches are currently being improved, however there are still issues like handling ambiguous code structures and supporting multiple programming languages.