{"title":"Do Programming Languages Affect Productivity? A Case Study Using Data from Open Source Projects","authors":"Daniel P. Delorey, C. Knutson, S. Chun","doi":"10.1109/FLOSS.2007.5","DOIUrl":null,"url":null,"abstract":"Brooks and others long ago suggested that on average computer programmers write the same number of lines of code in a given amount of time regardless of the programming language used. We examine data collected from the CVS repositories of 9,999 open source projects hosted on SourceForge.net to test this assumption for 10 of the most popular programming languages in use in the open source community. We find that for 24 of the 45 pairwise comparisons, the programming language is a significant factor in determining the rate at which source code is written, even after accounting for variations between programmers and projects.","PeriodicalId":383068,"journal":{"name":"First International Workshop on Emerging Trends in FLOSS Research and Development (FLOSS'07: ICSE Workshops 2007)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"39","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"First International Workshop on Emerging Trends in FLOSS Research and Development (FLOSS'07: ICSE Workshops 2007)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FLOSS.2007.5","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 39
Abstract
Brooks and others long ago suggested that on average computer programmers write the same number of lines of code in a given amount of time regardless of the programming language used. We examine data collected from the CVS repositories of 9,999 open source projects hosted on SourceForge.net to test this assumption for 10 of the most popular programming languages in use in the open source community. We find that for 24 of the 45 pairwise comparisons, the programming language is a significant factor in determining the rate at which source code is written, even after accounting for variations between programmers and projects.
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