Deep intellisense: a tool for rehydrating evaporated information
Deep intellisense: a tool for rehydrating evaporated information
复制标题
深度智能感知：补充蒸发信息的工具
DOI：
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发表时间：
2008
期刊：
影响因子：
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通讯作者：
Andrew Begel
中科院分区：
文献类型：
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作者：
Reid Holmes;Andrew Begel
在大型团队中工作的软件工程师很难理解为什么源代码看起来是这样的。通常，他们通过查看源代码的过去修订、错误报告、代码签入、邮件列表消息和其他文档来回答他们的问题。这种调查过程可能效率很低，特别是当他们寻求的答案位于由多个独立调查工具访问的孤立存储库中时。以前的挖掘方法都集中在将各种数据存储库连接在一起，在本文中，我们研究了显示从存储库中提取的信息的技术，以帮助开发人员建立一个有凝聚力的心理模型的代码背后的理由。在采访了几位开发人员和测试人员关于他们如何调查源代码之后，我们创建了一个名为Deep Intellisense的Visual Studio插件，它总结并显示了有关源代码的历史信息。我们设计了Deep Intelligensense，以解决工程师在当前技术中面临的许多障碍，并帮助他们花更少的时间收集信息，花更多的时间完成工作。
Software engineers working in large teams on large, long-lived code-bases have trouble understanding why the source code looks the way does. Often, they answer their questions by looking at past revisions of the source code, bug reports, code checkins, mailing list messages, and other documentation. This process of inquiry can be quite inefficient, especially when the answers they seek are located in isolated repositories accessed by multiple independent investigation tools. Prior mining approaches have focused on linking various data repositories together; in this paper we investigate techniques for displaying information extracted from the repositories in a way that helps developers to build a cohesive mental model of the rationale behind the code. After interviewing several developers and testers about how they investigate source code, we created a Visual Studio plugin called Deep Intellisense that summarizes and displays historical information about source code. We designed Deep Intellisense to address many of the hurdles engineers face with their current techniques, and help them spend less time gathering information and more time getting their work done.