Estimating Defect Density Using Test Coverage

Defect density is one of the most important factors that allow one to decide if a piece of software is ready to be released. In theory, one can find all the defects and count them, however it is impossible to find all the defects within any reasonable amount of time. Estimating defect density can become difficult for high reliability software, since the remaining defects can be extremely hard to test. Defect seeding will work only if the distribution of seeded defects is similar to the existing defects. One possible way is to apply the exponential SRGM and thus estimate the total number of defects present at the beginning of testing. Here we show the problems with this approach and present a new approach based on software test coverage. Software test coverage directly measures the thoroughness of testing avoiding the problem of variations of test effectiveness. Here we present interpretations of the parameters of the coveragedefect-density model presented by Malaiya et al. We apply this model to actual test data to project the residual defect density. The results show that this method results in estimates that are more stable than the existing methods. This method is easier to understand and the convergence to the estimate can be visually observed.