Proceedings of the 16th ACM / IEEE International Symposium on Empirical Software Engineering and Measurement最新文献

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Only Time Will Tell: Modelling Information Diffusion in Code Review with Time-Varying Hypergraphs 只有时间会告诉我们:用时变超图建模代码审查中的信息扩散

Proceedings of the 16th ACM / IEEE International Symposium on Empirical Software Engineering and Measurement Pub Date : 2021-10-14 DOI: 10.1145/3544902.3546254

Michael Dorner, Darja Šmite, D. Méndez, K. Wnuk, J. Czerwonka

{"title":"Only Time Will Tell: Modelling Information Diffusion in Code Review with Time-Varying Hypergraphs","authors":"Michael Dorner, Darja Šmite, D. Méndez, K. Wnuk, J. Czerwonka","doi":"10.1145/3544902.3546254","DOIUrl":"https://doi.org/10.1145/3544902.3546254","url":null,"abstract":"Background: Modern code review is expected to facilitate knowledge sharing: All relevant information, the collective expertise, and meta-information around the code change and its context become evident, transparent, and explicit in the corresponding code review discussion. The discussion participants can leverage this information in the following code reviews; the information diffuses through the communication network that emerges from code review. Traditional time-aggregated graphs fall short in rendering information diffusion as those models ignore the temporal order of the information exchange: Information can only be passed on if it is available in the first place. Aim: This manuscript presents a novel model based on time-varying hypergraphs for rendering information diffusion that overcomes the inherent limitations of traditional, time-aggregated graph-based models. Method: In an in-silico experiment, we simulate an information diffusion within the internal code review at Microsoft and show the empirical impact of time on a key characteristic of information diffusion: the number of reachable participants. Results: Time-aggregation significantly overestimates the paths of information diffusion available in communication networks and, thus, is neither precise nor accurate for modelling and measuring the spread of information within communication networks that emerge from code review. Conclusion: Our model overcomes the inherent limitations of traditional, static or time-aggregated, graph-based communication models and sheds the first light on information diffusion through code review. We believe that our model can serve as a foundation for understanding, measuring, managing, and improving knowledge sharing in code review in particular and information diffusion in software engineering in general.","PeriodicalId":220679,"journal":{"name":"Proceedings of the 16th ACM / IEEE International Symposium on Empirical Software Engineering and Measurement","volume":"144 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131902360","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Proceedings of the 16th ACM / IEEE International Symposium on Empirical Software Engineering and Measurement 第16届ACM / IEEE经验软件工程与测量国际研讨会论文集

Proceedings of the 16th ACM / IEEE International Symposium on Empirical Software Engineering and Measurement Pub Date : 2014-09-18 DOI: 10.1145/2652524

M. Morisio, T. Dybå, Marco Torchiano

引用次数: 8

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