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<p>Previously, many researchers proposed various software reliability growth model (SRGM) to evaluate software reliability. Also, they applied SRGM to open source software (OSS). On the other hand, almost all OSS continuing to develop. In this case, OSS’s latent faults fluctuates frequently. Moreover, it is difficult to evaluate accurately because this doesn’t consider by SRGM assumptions. It is known that as the number of software users increases, the number of the detected faults tends to increase. Especially, it is seen in like the number of the users changes fluctuates and the software update. In this paper, we analyze the impact of fluctuations in the number of software users on OSS using actual data from a fault tracking system. Moreover, we review the assumptions of non-homogeneous Poisson process (NHPP) based SRGM and propose the corrected time for model considering the number of number of users. Furthermore, we applied propose model to existing general NHPP-based SRGM’s mean value function. As a result, we confirmed that the number of users increases effect to the number of the detected faults. Furthermore, the propose model can evaluate software reliability accurately. Especially, logarithmic Poisson SRGM shows the highest estimation result.</p>

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A NHPP-based SRGM considering the number of users for OSS

  • 期刊论文

  • 发表日期：

    2025年5月17日

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  • Shoichiro Miyamoto,
  • Lei Zhou,
  • Yoshinobu Tamura,
  • Shigeru Yamada

摘要

Previously, many researchers proposed various software reliability growth model (SRGM) to evaluate software reliability. Also, they applied SRGM to open source software (OSS). On the other hand, almost all OSS continuing to develop. In this case, OSS’s latent faults fluctuates frequently. Moreover, it is difficult to evaluate accurately because this doesn’t consider by SRGM assumptions. It is known that as the number of software users increases, the number of the detected faults tends to increase. Especially, it is seen in like the number of the users changes fluctuates and the software update. In this paper, we analyze the impact of fluctuations in the number of software users on OSS using actual data from a fault tracking system. Moreover, we review the assumptions of non-homogeneous Poisson process (NHPP) based SRGM and propose the corrected time for model considering the number of number of users. Furthermore, we applied propose model to existing general NHPP-based SRGM’s mean value function. As a result, we confirmed that the number of users increases effect to the number of the detected faults. Furthermore, the propose model can evaluate software reliability accurately. Especially, logarithmic Poisson SRGM shows the highest estimation result.