How do you effectively track technical debt? [closed]

Question

In your practice, how do you effectively track and manage technical debt?

Is there a specific metric, like SLOC, that you use?

How do you visually display your results to stakeholders and management?

What benefits have you seen in the process?

Answer 1

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 :)

Answer 2

We use @todo comments.

In Python, the epydoc tools format the @todo nicely.

We have a little code scanner that extracts the @todo comment lines. We push them into the backlog as work to be done.

Answer 3

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/

Answer 4

There is a plug-in for Sonar that translates technical debt into $.

I haven't used it myself yet, but it looks promising.