Extracting Archival-Quality Information from Software-Related Chats
Extracting Archival-Quality Information from Software-Related Chats
复制标题
从软件相关的聊天中提取档案质量信息
DOI：
10.1145/3377812.3381391
复制
发表时间：
2020
期刊：
影响因子：
--
通讯作者：
Chatterjee, Preetha
中科院分区：
文献类型：
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作者：
Chatterjee, Preetha
软件开发人员越来越多地通过在线聊天服务就软件开发进行对话。许多聊天通信都包含有价值的信息，例如代码描述、良好的编程实践以及常见错误/异常的原因。然而，聊天社区内容的性质是短暂的，这与电子邮件、错误报告和问答论坛等其他开发人员通信的存档性质相反。结果，随着时间的推移，重要的信息和建议会丢失。本论文的重点是从软件相关的聊天中提取存档信息，具体来说是（1）自动识别包含存档质量信息的对话，（2）准确地降低作为存档信息报告的信息的粒度，以及（3）进行案例研究，以调查从聊天中提取的存档质量信息与问答论坛中的相关帖子相比如何。开发人员聊天中的归档知识可用于多种应用程序，例如：创建可供给定聊天社区使用的新归档机制、增强问答论坛或促进特定信息的挖掘并改进软件维护工具。
Software developers are increasingly having conversations about software development via online chat services. Many of those chat communications contain valuable information, such as code descriptions, good programming practices, and causes of common errors/exceptions. However, the nature of chat community content is transient, as opposed to the archival nature of other developer communications such as email, bug reports and Q&A forums. As a result, important information and advice are lost over time.The focus of this dissertation isExtracting Archival Information from Software-Related Chats, specifically to (1) automatically identify conversations that contain archival-quality information, (2) accurately reduce the granularity of the information reported as archival information, and (3) conduct a case study to investigate how archival quality information extracted from chats compare to related posts in Q&A forums. Archiving knowledge from developer chats could be used potentially in several applications such as: creating a new archival mechanism available to a given chat community, augmenting Q&A forums, or facilitating the mining of specific information and improving software maintenance tools.
自由软件开发人员作为职业社区：解决冲突并促进协作
DOI：
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发表时间：
2003
期刊：
Group
影响因子：
--
作者：
M. Elliott;W. Scacchi
通讯作者：
W. Scacchi