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Application of Fuzzy Time Series in Prediction of Time Between Failures & Faults in Software Reliability Assessment

机译:模糊时间序列在软件可靠性评估中故障与故障之间的时间预测中的应用

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摘要

Since last seventies, various software reliability growth models (SRGMs) have been developed to estimate different measures related to quality of software like: number of remaining faults, software failure rate, reliability, cost, release time, etc. Most of the exiting SRGMs are probabilistic. These models have been developed based on various assumptions. The entire software development process is performed by human being. Also, a software can be executed in different environments. As human behavior is fuzzy and the environment is changing, the concept of fuzzy set theory is applicable in developing software reliability models. In this paper, two fuzzy time series based software reliability models have been proposed. The first one predicts the time between failures (TBFs) of software and the second one predicts the number of errors present in software. Both the models have been developed considering the software failure data as linguistic variable. Usefulness of the models has been demonstrated using real failure data.
机译:从上个世纪七十年代开始,已经开发了各种软件可靠性增长模型(SRGM)来估计与软件质量相关的不同度量,例如:剩余故障数,软件故障率,可靠性,成本,发布时间等。大多数现有SRGM是概率的。这些模型是根据各种假设开发的。整个软件开发过程是由人执行的。另外,可以在不同的环境中执行软件。由于人类行为是模糊的并且环境在变化,因此模糊集理论的概念适用于开发软件可靠性模型。本文提出了两种基于模糊时间序列的软件可靠性模型。第一个预测软件的故障间隔时间(TBF),第二个预测软件中出现的错误数量。两种模型都是以软件故障数据作为语言变量来开发的。使用实际的故障数据已经证明了模型的实用性。

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