Leveraging software analytics to maximize developer productivity during software maintenance.

软件从业者根据他们对软件系统的理解做出技术和业务决策。这种理解是基于他们自己的经验，但是可以通过研究各种开发工件（包括源代码、错误报告、版本控制元数据、测试用例、使用日志等）来增强。不幸的是，这些工件中包含的信息通常没有按照对开发人员的日常决策需要立即有用的方式进行组织。为了处理大量数据，许多从业者和研究人员转向了分析。

Software practitioners make technical and business decisions based on the understanding they have of their software systems. This understanding is grounded in their own experiences, but can be augmented by studying various kinds of development artifacts, including source code, bug reports, version control meta-data, test cases, usage logs, etc. Unfortunately, the information contained in these artifacts is typically not organized in the way that is immediately useful to developers' everyday decision making needs. To handle the large volumes of data, many practitioners and researchers have turned to analytics.