Abstract: In order to overcome the oversimplified treatment of the defect discovery rate in the traditional G-O (Goel-Okumoto) software reliability model, an improved model that more accurately describes the actual change of the defect discovery rate over time is proposed. Unlike the conventional assumption that it is treated as a constant or monotonic function, the improved model considers the progress of testers’ learning and debugging capabilities and the inherent tendency of the software’s defect discovery rate to decrease over time. Therefore, it assumes that the defect discovery rate first increases before showing a dynamic trend of decline. The model’s effectiveness is verified by applying it to two sets of public software defect detectionda tasets and comparing it with a variety of classic models. Experimental results confirm that the improved G-O model demonstrates excellent performance in both fitting and prediction capabilities, proving its applicability and superiority in software reliability assessment.

Key words: softwarereliability model, defect discovery rate, Goel-Okumoto(G-O) model, parameter estimation