Software reliability growth models (SRGMs) based on a nonhomogeneous Poisson process (NHPP) are widely used to describe the stochastic failure behavior and assess the reliability of software systems. For these models, the testing-effort effect and the fault interdependency play significant roles. Considering a power-law function of testing effort and the interdependency of multigeneration faults, we propose a modified SRGM to reconsider the reliability of open source software (OSS) systems and then to validate the model’s performance using several real-world data. Our empirical experiments show that the model well fits the failure data and presents a high-level prediction capability. We also formally examine the optimal policy of software release, considering both the testing cost and the reliability requirement. By conducting sensitivity analysis, we find that if the testing-effort effect or the fault interdependency was ignored, the best time to release software would be seriously delayed and more resources would be misplaced in testing the software.
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Background Although pneumonia is a leading cause of death in New York City (NYC), limited data exist about the settings in which pneumonia ...
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Summary We tested whether prophylactic droperidol and ondansetron, in combination with a moderate dose of dexamethasone, were equally effe...
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by Demin Li, Carol Bentley, Jenna Yates, Maryam Salimi, Jenny Greig, Sarah Wiblin, Tasneem Hassanali, Alison H. Banham Therapeutic monoclon...
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Abstract Dermoscopy has demonstrated clinical benefits in improving early melanoma diagnosis and reducing unnecessary biopsies. Despite th...
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