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Does anyone know if there is some kind of tool to put a number on technical debt of a code base, as a kind of code metric? If not, is anyone aware of an algorithm or set of heuristics for it?

If neither of those things exists so far, I'd be interested in ideas for how to get started with such a thing. That is, how can I quantify the technical debt incurred by a method, a class, a namespace, an assembly, etc. I'm most interested in analyzing and assessing a C# code base, but please feel free to chime in for other languages as well, particularly if the concepts are language transcendent. I would argue (in the context of the metaphor of debt) that managers may be the debt-holders, but the code artifacts represent the debt valuation and could be quantified. That is, I agree that managers may make a decision like 'forget unit testing because we don't have time' and thus incur technical debt. But, I certainly think you can put a number to individual code elements as a heuristic. Think of it this way - if management makes a series of horrible decisions for the future, but no code has been written, is there any debt at that moment?

– Feb 20 '12 at 19:25 •. Measuring technical debt is hard, plus it confuses managers.

However, I can tell you a good way to fight technical debt: cheap, nice and working prototypes, particularly if the code base revolves around GUI. As Joel suggested here:, spend a bit of time each day cleaning things up. The change must be positive improvements, not 'OMG, our technical debt = pentablobs and it is rising exponentially at a rate of. Full hd movies download 1080p hindi. The sky is falling.' Just spend a bit of time each day on kaizen in a way that does not break things that work. Make friends.

SonarQube (formerly Sonar) is an open-source platform developed by SonarSource for. 'Creating a Sonar Plugin for software development metrics'. CAST AIP analyzes source code by categorizing each business function into a measurable unit. This allows for faster identification of reduced software quality, system vulnerabilities, and areas where productivity can be improved in a complex, multi-tiered infrastructure.

– Feb 20 '12 at 20:22 •. Technical debt is just an abstract idea that, somewhere along the lines of designing, building, testing, and maintaining a system, certain decisions were made such that the product has become more difficult to test and maintain. Having more technical debt means that it will become more difficult to continue to develop a system - you either need to cope with the technical debt and allocate more and more time for what would otherwise be simple tasks, or you need to invest resources (time and money) into reducing technical debt by refactoring the code, improving the tests, and so on. There are a number of metrics that might give you some indication as to the quality of the code: • Code coverage.

There that tell you what percentage of your functions, statements, and lines are covered by unit tests. You can also map system and acceptance tests back to requirements to determine the percentage of requirements covered by a system-level test. The appropriate coverage depends on the nature of the application. Code that exhibits low coupling and high cohesion is typically easier to read, understand, and test. There are code analysis tools that can report the amount of coupling and cohesion in a given system. • is the number of unique paths through an application. It's typically counted at the method/function level.