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Fault density: so costly to calculate that few values are reliable

Fault density (i.e., number of faults per thousand lines of code) often appears in claims relating to software quality.

Fault density sounds like a very useful value to know; unfortunately most quoted values are meaningless and because obtaining reliable data is very costly.

The starting point for calculating fault density is the number of reported faults (I will leave the complexity of what constitutes a line of code for a future post). Most faults don’t get reported.

If there are no reported faults, fault density is zero. The more often software is executed the more likely a fault will be experienced (i.e., the large the range of input values thrown at a program the more likely it will go down a path containing a fault). Comparing like-with-like requires knowing how many different kinds of input a program processed to experience a given number of faults; we don’t want to fall into the trap of claiming heavily used code is less fault prone than lightly used code.

What counts as a fault? One study found that 46% of reported faults in Open Source bug tracking systems were misclassified (e.g., a fault report was actually a request for enhancement). Again, comparing like-with-like requires agreement on what constitutes a fault.

How should faults in code that is no longer shipped be counted? If the current version of a program contains 100K lines and previous versions contained 50K lines that have been deleted, should the faults in those 50K lines contribute to the fault density of the current program? I would say not, which means somebody has to figure out which reported faults apply to code in the current version of the program.

I am aware of less than half a dozen fault density values that I would consider reliable (most calculated during the Rome period). Everything else is little better than reading tea-leafs.

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