Under CopyrightBriand, L.C.L.C.BriandEmam, K. elK. elEmamFreimut, B.B.Freimut2022-03-0709.08.20001998https://publica.fraunhofer.de/handle/publica/28949310.24406/publica-fhg-289493In order to control inspections, the number of remaining defects in software artifacts after their inspection should be estimated. This would allow, for example, deciding whether a reinspection of supposedly faulty artefacts is necessary. Several studies in software engineering have considered capture-recapture models for performing such estimations. These models were initially developed for estimating animal abundance in wildlife research. In addition to these models, researchers in software engineering have recently proposed a procedure, namely the Detection Profile Method (DPM), that makes less restrictive assumptions than some capture-recapture models and that show promise in terms of estimation accuracy. In this study, we investigate the combination of DPM with capture-recapture models to address a practical difficulty when applying capture-recapture models alone: extreme under/over estimation. The existence of such extreme outliers provided by capture-recapture models can discour age their use because their consequences in terms of wasted effort of defect slippage can be substantial, and therefore it is not clear whether a particular estimate can be trusted. We identify a hybrid approach, using both capture-recapture models and DPM, and evaluate it using actual inspection data. Our results indicate that this hybrid approach has the same accuracy as capture-recapture models alone and DPM alone, and most importantly does not exhibit extreme over/under estimation. This new approach can be used in practice with a high degree of confidence since its estimates are not likely to exhibit extreme estimation error.encapture-recapture modeldefect content estimationsoftware inspection004005006report