{"title":"CodeCAM: capturing programmer's reaction during coding session","authors":"Yusuke Shinyama, Yoshitaka Arahori, K. Gondow","doi":"10.1109/MAINT.2018.8323087","DOIUrl":null,"url":null,"abstract":"Software development has been plagued with the lack of documentation. We focus on ways to augment existing code comments with various external data sources such as a developer’s monologue or facial expression, allowing its user to track the accompanying non-textual information from a final source code. We propose CodeCAM, a framework to capture a developer’s reaction as well as its complete screenshot during a coding session as a video stream. A novel method is introduced to associate these streams with the corresponding portion of a source code. Our method does not require modifying existing tools or IDEs. We then applied facial expression analysis in attempt to capture a developer’s sentiment toward the source code during its development. Our preliminary experiments revealed that a developer tends to make a certain type of face (e.g. puzzled) when dealing with a difficult part of a program.","PeriodicalId":206704,"journal":{"name":"2018 IEEE Workshop on Mining and Analyzing Interaction Histories (MAINT)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE Workshop on Mining and Analyzing Interaction Histories (MAINT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MAINT.2018.8323087","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Software development has been plagued with the lack of documentation. We focus on ways to augment existing code comments with various external data sources such as a developer’s monologue or facial expression, allowing its user to track the accompanying non-textual information from a final source code. We propose CodeCAM, a framework to capture a developer’s reaction as well as its complete screenshot during a coding session as a video stream. A novel method is introduced to associate these streams with the corresponding portion of a source code. Our method does not require modifying existing tools or IDEs. We then applied facial expression analysis in attempt to capture a developer’s sentiment toward the source code during its development. Our preliminary experiments revealed that a developer tends to make a certain type of face (e.g. puzzled) when dealing with a difficult part of a program.