Vaibhav Bajpai, A. Brunström, A. Feldmann, W. Kellerer, A. Pras, H. Schulzrinne, Georgios Smaragdakis, Matthias Wählisch, Klaus Wehrle
{"title":"Dagstuhl初学者指南再现性的实验网络研究","authors":"Vaibhav Bajpai, A. Brunström, A. Feldmann, W. Kellerer, A. Pras, H. Schulzrinne, Georgios Smaragdakis, Matthias Wählisch, Klaus Wehrle","doi":"10.1145/3314212.3314217","DOIUrl":null,"url":null,"abstract":"Reproducibility is one of the key characteristics of good science, but hard to achieve for experimental disciplines like Internet measurements and networked systems. This guide provides advice to researchers, particularly those new to the field, on designing experiments so that their work is more likely to be reproducible and to serve as a foundation for follow-on work by others.","PeriodicalId":403234,"journal":{"name":"Comput. Commun. Rev.","volume":"8 1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"44","resultStr":"{\"title\":\"The Dagstuhl beginners guide to reproducibility for experimental networking research\",\"authors\":\"Vaibhav Bajpai, A. Brunström, A. Feldmann, W. Kellerer, A. Pras, H. Schulzrinne, Georgios Smaragdakis, Matthias Wählisch, Klaus Wehrle\",\"doi\":\"10.1145/3314212.3314217\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Reproducibility is one of the key characteristics of good science, but hard to achieve for experimental disciplines like Internet measurements and networked systems. This guide provides advice to researchers, particularly those new to the field, on designing experiments so that their work is more likely to be reproducible and to serve as a foundation for follow-on work by others.\",\"PeriodicalId\":403234,\"journal\":{\"name\":\"Comput. Commun. Rev.\",\"volume\":\"8 1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-01-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"44\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Comput. Commun. Rev.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3314212.3314217\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Comput. Commun. Rev.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3314212.3314217","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The Dagstuhl beginners guide to reproducibility for experimental networking research
Reproducibility is one of the key characteristics of good science, but hard to achieve for experimental disciplines like Internet measurements and networked systems. This guide provides advice to researchers, particularly those new to the field, on designing experiments so that their work is more likely to be reproducible and to serve as a foundation for follow-on work by others.