Automating the removal of obsolete TODO comments

Zhipeng Gao, Xin Xia, David Lo, John Grundy, Thomas Zimmermann

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

5 Citations (Scopus)

Abstract

TODO comments are very widely used by software developers to describe their pending tasks during software development. However, after performing the task developers sometimes neglect or simply forget to remove the TODO comment, resulting in obsolete TODO comments. These obsolete TODO comments can confuse development teams and may cause the introduction of bugs in the future, decreasing the software's quality and maintainability. Manually identifying obsolete TODO comments is time-consuming and expensive. It is thus necessary to detect obsolete TODO comments and remove them automatically before they cause any unwanted side effects. In this work, we propose a novel model, named TDCleaner, to identify obsolete TODO comments in software projects. TDCleaner can assist developers in just-in-time checking of TODO comments status and avoid leaving obsolete TODO comments. Our approach has two main stages: offline learning and online prediction. During offline learning, we first automatically establish <code_change, todo_comment, commit_msg> training samples and leverage three neural encoders to capture the semantic features of TODO comment, code change and commit message respectively. TDCleaner then automatically learns the correlations and interactions between different encoders to estimate the final status of the TODO comment. For online prediction, we check a TODO comment's status by leveraging the offline trained model to judge the TODO comment's likelihood of being obsolete. We built our dataset by collecting TODO comments from the top-10,000 Python and Java Github repositories and evaluated TDCleaner on them. Extensive experimental results show the promising performance of our model over a set of benchmarks. We also performed an in-the-wild evaluation with real-world software projects, we reported 18 obsolete TODO comments identified by TDCleaner to Github developers and 9 of them have already been confirmed and removed by the developers, demonstrating the practical usage of our approach.

Original languageEnglish
Title of host publicationProceedings of the 29th ACM Joint Meeting European Software Engineering Conference and Symposium on the Foundations of Software Engineering
EditorsDiomidis Spinellis, Georgios Gousios, Marsha Chechik, Massimiliano Di Penta
Place of PublicationNew York NY USA
PublisherAssociation for Computing Machinery (ACM)
Pages218-229
Number of pages12
ISBN (Electronic)9781450385626
DOIs
Publication statusPublished - 2021
EventJoint Meeting of the European Software Engineering Conference and the ACM SIGSOFT Symposium on the Foundations of Software Engineering 2021 - Online, Athens, Greece
Duration: 23 Aug 202128 Aug 2021
Conference number: 29th
https://dl.acm.org/doi/proceedings/10.1145/3468264 (Proceedings)
https://2021.esec-fse.org (Website)

Conference

ConferenceJoint Meeting of the European Software Engineering Conference and the ACM SIGSOFT Symposium on the Foundations of Software Engineering 2021
Abbreviated titleESEC/FSE 2021
Country/TerritoryGreece
CityAthens
Period23/08/2128/08/21
Internet address

Keywords

  • Bert
  • Code-Comment Inconsistency
  • TODO comment

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