Bill Clark’s analysis and taxonomy of tech debt useful for framing discussions of tech debt and making the best use of limited resources.
When measuring a piece of tech debt, you can use impact (to customers and to developers), fix cost (time and risk), and contagion. I believe most developers regularly consider impact and fix cost, while I’ve rarely encountered discussions of contagion. Contagion can be a developer’s worst enemy as a problem burrows in and becomes harder and harder to dislodge. It is possible, however, to turn contagion into a weapon by making your fix more contagious than the problem.
Working on League, most of the tech debt I’ve seen falls into one of the 4 categories I’ve presented here. Local debt, like a black box of gross. MacGyver debt, where 2 or more systems are duct-taped together with conversion functions. Foundational debt, when the entire structure is built on some unfortunate assumptions. Data debt, when enormous quantities of data are piled on some other type of debt, making it risky and time-consuming to fix.