Software reliability growth models (SRGMs) based on a nonhomogeneous Poisson process (NHPP) are widely used to describe\nthe stochastic failure behavior and assess the reliability of software systems. For these models, the testing-effort effect and the\nfault interdependency play significant roles. Considering a power-law function of testing effort and the interdependency of\nmultigeneration faults, we propose amodified SRGMto reconsider the reliability of open source software (OSS) systems and then to\nvalidate the model�s performance using several real-world data. Our empirical experiments show that the model well fits the failure\ndata and presents a high-level prediction capability. We also formally examine the optimal policy of software release, considering\nboth the testing cost and the reliability requirement. By conducting sensitivity analysis, we find that if the testing-effort effect or\nthe fault interdependency was ignored, the best time to release software would be seriously delayed and more resources would be\nmisplaced in testing the software.
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