Utkarsh Desai, G. Sridhara, Srikanth G. Tamilselvam
{"title":"Advances in Code Summarization","authors":"Utkarsh Desai, G. Sridhara, Srikanth G. Tamilselvam","doi":"10.1109/ICSE-Companion52605.2021.00141","DOIUrl":null,"url":null,"abstract":"Several studies have suggested that comments describing source code can help mitigate the burden of program understanding. However, software systems usually lack adequate comments and even when present, the comments may be obsolete or unhelpful. Researchers have addressed this issue by automatically generating comments from source code, a task referred to as Code Summarization. In this technical presentation, we take a deeper look at some of the significant, recent works in the area of code summarization and how each of them attempts to take a new perspective of this task including methods leveraging RNNs, Transformers, Graph neural networks and Reinforcement learning.","PeriodicalId":136929,"journal":{"name":"2021 IEEE/ACM 43rd International Conference on Software Engineering: Companion Proceedings (ICSE-Companion)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE/ACM 43rd International Conference on Software Engineering: Companion Proceedings (ICSE-Companion)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSE-Companion52605.2021.00141","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
Several studies have suggested that comments describing source code can help mitigate the burden of program understanding. However, software systems usually lack adequate comments and even when present, the comments may be obsolete or unhelpful. Researchers have addressed this issue by automatically generating comments from source code, a task referred to as Code Summarization. In this technical presentation, we take a deeper look at some of the significant, recent works in the area of code summarization and how each of them attempts to take a new perspective of this task including methods leveraging RNNs, Transformers, Graph neural networks and Reinforcement learning.