{"title":"用于表示开源软件中开发人员专业知识的复制包","authors":"Tapajit Dey, Andrey Karnauch, A. Mockus","doi":"10.1109/ICSE-Companion52605.2021.00109","DOIUrl":null,"url":null,"abstract":"This describes the artifact associated with the article \"Representation of Developer Expertise in Open Source Software\" at the International Conference on Software Engineering 2021. The aim of the original paper was to define afeasible representation of adeveloper's expertise in specific focus areas of software development by gauging their fluency with different sets of APIs. The artifact is made available through Zenodo under the CC-BY-4.0 license at https://doi.org/10.5281/zenodo.4457107. The README file has detailed instructions on how to replicate the results presented in the original paper. The artifact includes the input dataset (with the developers' names and email addresses replaced by their corresponding SHA1 digest values to protect privacy) and all the associated scripts. The trained Doc2Vec models are also included in the artifact. These models can be used to obtain the Skill Space representations of developers, projects, and APIs without having to re-train the model.","PeriodicalId":136929,"journal":{"name":"2021 IEEE/ACM 43rd International Conference on Software Engineering: Companion Proceedings (ICSE-Companion)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Replication Package for Representation of Developer Expertise in Open Source Software\",\"authors\":\"Tapajit Dey, Andrey Karnauch, A. Mockus\",\"doi\":\"10.1109/ICSE-Companion52605.2021.00109\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This describes the artifact associated with the article \\\"Representation of Developer Expertise in Open Source Software\\\" at the International Conference on Software Engineering 2021. The aim of the original paper was to define afeasible representation of adeveloper's expertise in specific focus areas of software development by gauging their fluency with different sets of APIs. The artifact is made available through Zenodo under the CC-BY-4.0 license at https://doi.org/10.5281/zenodo.4457107. The README file has detailed instructions on how to replicate the results presented in the original paper. The artifact includes the input dataset (with the developers' names and email addresses replaced by their corresponding SHA1 digest values to protect privacy) and all the associated scripts. The trained Doc2Vec models are also included in the artifact. These models can be used to obtain the Skill Space representations of developers, projects, and APIs without having to re-train the model.\",\"PeriodicalId\":136929,\"journal\":{\"name\":\"2021 IEEE/ACM 43rd International Conference on Software Engineering: Companion Proceedings (ICSE-Companion)\",\"volume\":\"38 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE/ACM 43rd International Conference on Software Engineering: Companion Proceedings (ICSE-Companion)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSE-Companion52605.2021.00109\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE/ACM 43rd International Conference on Software Engineering: Companion Proceedings (ICSE-Companion)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSE-Companion52605.2021.00109","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Replication Package for Representation of Developer Expertise in Open Source Software
This describes the artifact associated with the article "Representation of Developer Expertise in Open Source Software" at the International Conference on Software Engineering 2021. The aim of the original paper was to define afeasible representation of adeveloper's expertise in specific focus areas of software development by gauging their fluency with different sets of APIs. The artifact is made available through Zenodo under the CC-BY-4.0 license at https://doi.org/10.5281/zenodo.4457107. The README file has detailed instructions on how to replicate the results presented in the original paper. The artifact includes the input dataset (with the developers' names and email addresses replaced by their corresponding SHA1 digest values to protect privacy) and all the associated scripts. The trained Doc2Vec models are also included in the artifact. These models can be used to obtain the Skill Space representations of developers, projects, and APIs without having to re-train the model.