Using a reliability growth model to control software inspection

After a software inspection the project manager has to decide whether he can pass a product on to the next software development stage or whether it still contains a substantial number of defects and should be reinspected to further improve its quality. While a substantial number of defects remaining in a product after inspection is a reasonable precondition to schedule a reinspection, it is also important to estimate whether the likely number of defects to be found with a reinspection will lower the defect density under the target threshold. In this work we propose a reliability growth model and two heuristic linear models for software inspection, which estimate the likely number of additional defects to be found during reinspection. We evaluate the accuracy of these models with time-stamped defect data from a large-scale controlled inspection experiment on reinspection. Main findings are: (a) The two best models estimated the defect detection capability for reinspection with good accuracy: Over 80% of the estimates had an absolute relative error of under 10%; (b) The reinspection decision correctness based on the estimates of all investigated models, overall around 80% correct decisions, was much better than the trivial models to always or never reinspect; the latter is the default decision in practice.