L. Pascarella, Achyudh Ram, A. Nadeem, Dinesh Bisesser, Norman Knyazev, Alberto Bacchelli
{"title":"Investigating type declaration mismatches in Python","authors":"L. Pascarella, Achyudh Ram, A. Nadeem, Dinesh Bisesser, Norman Knyazev, Alberto Bacchelli","doi":"10.1109/MALTESQUE.2018.8368458","DOIUrl":null,"url":null,"abstract":"Past research provided evidence that developers making code changes sometimes omit to update the related documentation, thus creating inconsistencies that may contribute to faults and crashes. In dynamically typed languages, such as Python, an inconsistency in the documentation may lead to a mismatch in type declarations only visible at runtime. With our study, we investigate how often the documentation is inconsistent in a sample of 239 methods from five Python open-source software projects. Our results highlight that more than 20% of the comments are either partially defined or entirely missing and that almost 1% of the methods in the analyzed projects contain type inconsistencies. Based on these results, we create a tool, PyID, to early detect type mismatches in Python documentation and we evaluate its performance with our oracle.","PeriodicalId":345739,"journal":{"name":"2018 IEEE Workshop on Machine Learning Techniques for Software Quality Evaluation (MaLTeSQuE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE Workshop on Machine Learning Techniques for Software Quality Evaluation (MaLTeSQuE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MALTESQUE.2018.8368458","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
Past research provided evidence that developers making code changes sometimes omit to update the related documentation, thus creating inconsistencies that may contribute to faults and crashes. In dynamically typed languages, such as Python, an inconsistency in the documentation may lead to a mismatch in type declarations only visible at runtime. With our study, we investigate how often the documentation is inconsistent in a sample of 239 methods from five Python open-source software projects. Our results highlight that more than 20% of the comments are either partially defined or entirely missing and that almost 1% of the methods in the analyzed projects contain type inconsistencies. Based on these results, we create a tool, PyID, to early detect type mismatches in Python documentation and we evaluate its performance with our oracle.