I talk a little about some of the metrics used to identify technical debt in my blog entry below. Technical debt can mean much more than just code clean up items highlighted by TODO statements in code. The tracking mechanism will change depending on which risk indicator you're focused on.
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我们为技术债务编写故事卡。 它们是黑色的，上面有黄色的大警告标志。 墙上贴太多了，就很明显了。
任何走过的人都可以看到它们:)
We write story cards for technical debt. They are BLACK, with big yellow warning signs on them. Get too many on the wall, and it's REAL obvious.
Anyone who walks past can see them :)
我们使用
@todo注释。在 Python 中，epydoc 工具很好地格式化了
@todo。我们有一个小型代码扫描器，可以提取
@todo注释行。 我们将它们作为待完成的工作放入待办事项中。We use
@todocomments.In Python, the epydoc tools format the
@todonicely.We have a little code scanner that extracts the
@todocomment lines. We push them into the backlog as work to be done.我在下面的博客文章中讨论了一些用于识别技术债务的指标。 技术债务不仅仅意味着代码中 TODO 语句突出显示的代码清理项目。 跟踪机制将根据您关注的风险指标而变化。
http://blog.acrowire.com/technical-debt/技术债务-第 2 部分-识别/
I talk a little about some of the metrics used to identify technical debt in my blog entry below. Technical debt can mean much more than just code clean up items highlighted by TODO statements in code. The tracking mechanism will change depending on which risk indicator you're focused on.
http://blog.acrowire.com/technical-debt/technical-debt-part-2-identification/
有一个Sonar 插件可以翻译技术债务换成$。
我自己还没有使用过它，但看起来很有希望。
There is a plug-in for Sonar that translates technical debt into $.
I haven't used it myself yet, but it looks promising.